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Microbial diversity through an oceanographic lens: refining the concept of ocean provinces through trophic-level-specific analysis and productivity length-scales .
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Samples were processed using the dada2 pipeline with minor modifications:
primers were trimmed using cutadapt version 1.18 for full details see the scripts and sequencing statistics (Supplementary file gDoc)
within this script multiple subscripts are combined to make taxonomy, ASV count and metadata operatable and also subsetting for the different trophic level
## NOTE: Either Arial Narrow or Roboto Condensed fonts are required to use these themes.## Please use hrbrthemes::import_roboto_condensed() to install Roboto Condensed and## if Arial Narrow is not on your system, please see https://bit.ly/arialnarrow## Loading required package: viridisLite
#define oligotrophic and eutrophic provinces
L_CHL <- c("SATL-COLD", "SATL-HOT", "WTRA", "NATR")
H_CHL <- c("FKLD", "BRAZ", "CNRY", "NAST-E", "NADR")
source("C:/Users/choerstm/Documents/core_PS113/PrimaryProductivity/PP_analysis_ext.R", encoding = "UTF-8")sequencing + flow cytometry
Sequencing data is due to its technique compositional and needs normalization (Gloor et al. 2017)
hellinger:
standard transformation in ecological analyses- gives lower weight to low abundant taxa (e.g. https://doi.org/10.1093/femsre/fuw017) The transformation itself comprises dividing each value in a data matrix by its row sum, and taking the square root of the quotient. (Buttigieg PL, Ramette A (2014) A Guide to Statistical Analysis in Microbial Ecology: a community-focused, living review of multivariate data analyses. FEMS Microbiol Ecol. 90: 543–550.)
clr: The centered log-ratio (clr) transformation has been introduced by Aitchison (1986). Given an observation vector of D “counted” features (taxa, operational taxonomic units or OTUs, genes, etc.) in a sample, x = [x1, x2, …xD], the clr transformation for the sample can be obtained as follows: xclr = [log(x1/G(x)), log(x2/G(x)) . . . log(xD/G(x))], G(x) = D√x1 · x2 · … · xD G(x) is the geometric mean of x. The clr transformed values can be used as inputs for multivariate hypothesis testing using tools such as MANOVA, regression etc.
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/general_clr_hellinger_transformation.R")
#clr transformations
ASVCount_16S.tax.clr <- clr(ASVCount_16S.tax,3)#the 3 is the chosen rowsum cutoff## No. corrected values: 9644ASVCount_18S.tax.clr <- clr(ASVCount_18S.tax,3)## No. corrected values: 9336#aitchinson distance
ASV_Aitchinson_dist_16S <- dczm(ASVCount_16S.tax,3)## Loading required package: coda.base## Warning: package 'coda.base' was built under R version 4.0.5##
## Attaching package: 'coda.base'## The following object is masked from 'package:stats':
##
## dist## Loading required package: usedist## Warning: package 'usedist' was built under R version 4.0.5## No. corrected values: 9644ASV_Aitchinson_dist_18S <- dczm(ASVCount_18S.tax,3)## No. corrected values: 9336rationale for functional groups: trophic grouping based on literature. Note that within mixotrophic subsetting might be obligatory heterotrophs as the choosen resoultion is taxonomically not resolved on that level.
For more information see Table S7
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/autotrophs_subscript.R", encoding = "UTF-8")
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/mixotrophs_subset.R", encoding = "UTF-8")
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/heterotrophs_subset.R", encoding = "UTF-8")ASVCount_16S.tax.auto_ait <- dczm(ASVCount_16S.tax.auto, 3)## No. corrected values: 576ASVCount_18S.tax.auto_ait <- dczm(ASVCount_18S.tax.auto, 3)## No. corrected values: 5880ASVCount_18S.tax.mixo_ait <- dczm(ASVCount_mixo, 3)## No. corrected values: 1226ASVCount_16S.tax.het_ait <- dczm(ASVCount_16S.tax.het, 3)## No. corrected values: 10365ASVCount_18S.tax.het_ait <- dczm(ASVCount_18S.tax.het, 3)## No. corrected values: 8061use iNEXT package to calculate hill numbers 0-2.
iNEXT focuses on three measures of Hill numbers of order q: species richness (q = 0), Shannon diversity (q = 1, the exponential of Shannon entropy) and Simpson diversity (q = 2, the inverse of Simpson concentration). For each diversity measure, iNEXT uses the observed sample of abundance or incidence data (called the “reference sample”) to compute diversity estimates and the associated 95% confidence intervals for the following two types of rarefaction and extrapolation (R/E):
Sample‐size‐based R/E sampling curves: iNEXT computes diversity estimates for rarefied and extrapolated samples up to an appropriate size. This type of sampling curve plots the diversity estimates with respect to sample size.
Coverage‐based R/E sampling curves: iNEXT computes diversity estimates for rarefied and extrapolated samples with sample completeness (as measured by sample coverage) up to an appropriate coverage. This type of sampling curve plots the diversity estimates with respect to sample coverage.
iNEXT also plots the above two types of sampling curves and a sample completeness curve. The sample completeness curve provides a bridge between these two types of curves.
As a good compromise between richness and evenness we proceed with shannon diversity (q=1) in the following analyses
## Loading required package: iNEXT## [1] '2.0.20'
## [1] '2.0.20'
## [1] '2.0.20'
## [1] '2.0.20'
## [1] '2.0.20'
## [1] '2.0.20'
## [1] '2.0.20'## Warning: 'dplyr' namespace cannot be unloaded:
## namespace 'dplyr' is imported by 'broom', 'tidyr', 'dbplyr' so cannot be unloadedsubset those samples where we have primary productivity metadata
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/primary_productivity_subsetting.R", encoding = "UTF-8")
rm(PP_averaged_province)add the travel calculations to the meta functions
pp_data <- c("Station_n", "biomass_transport", "specific_PP", "specific_PP_mol")
meta_functions.PP$Station_n <- as.character(gsub("PS113.S", "", meta_functions.PP$Site))
N_averaged$Station_n <- as.character(N_averaged$Station)
meta_functions.PP <- dplyr::inner_join(meta_functions.PP, N_averaged[pp_data], by="Station_n")
rm(pp_data)z scoring needs to be done when metadata with different value distributions are done. in z-scoring the mean of the datavaraible is shifted to 0.
histograms of selected metadata to check for normal distribution. 
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/z-scoring_subset.R")##
## Pearson's product-moment correlation
##
## data: N_averaged$mean_c.fix and N_averaged$mean_chla
## t = 4.8301, df = 78, p-value = 6.678e-06
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.2907722 0.6328326
## sample estimates:
## cor
## 0.4798337
##
##
## Pearson's product-moment correlation
##
## data: WTRA$mean_c.fix and WTRA$mean_chla
## t = 0.22558, df = 9, p-value = 0.8266
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.5496146 0.6458087
## sample estimates:
## cor
## 0.07498201
##
## # A tibble: 17 x 22
## Station mean_c.fix std mean_chla std_chla mean_cUptake Replicate Enriched
## <int> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <chr>
## 1 133 214. 9.69 0.586 0 0.0308 1 PP234
## 2 135 144. 3.35 0.779 0 0.0207 1 PP239
## 3 137 108. 1.32 0.635 0 0.0155 1 PP244
## 4 139 187. 5.07 0.546 0 0.0270 1 PP249
## 5 141 81.3 13.3 0.283 0 0.0117 1 PP254
## 6 143 81.8 46.7 0.562 0 0.0118 1 PP259
## 7 145 163. 1.99 0.962 0 0.0235 1 PP264
## 8 147 235. 41.7 0.583 0 0.0338 1 PP269
## 9 149 129. 14.9 0.590 0 0.0186 1 PP274
## 10 151 208. 8.31 1.22 0 0.0299 1 PP279
## 11 153 34.8 1.36 0.220 0 0.00501 1 PP284
## 12 155 56.6 4.00 0.447 0 0.00815 1 PP289
## 13 157 80.5 1.25 0.431 0 0.0116 1 PP294
## 14 159 23.6 0.935 0.163 0 0.00339 1 PP299
## 15 162 21.0 1.69 0.137 0 0.00303 1 PP304
## 16 164 18.8 0.238 0.129 0 0.00270 1 PP309
## 17 166 12.8 0.406 0.128 0 0.00184 1 PP314
## # ... with 14 more variables: Date <chr>, time.UTC. <chr>, Lat <dbl>,
## # Lon <dbl>, province <chr>, adcp_avg_e <dbl>, adcp_avg_n <dbl>,
## # adcp_horiz <dbl>, adcp_direc <dbl>, Station_m <chr>,
## # biomass_transport <dbl>, specific_PP <dbl>, specific_PP_mol <dbl>,
## # Station_n <chr>
##
## Wilcoxon rank sum test with continuity correction
##
## data: CNRY$mean_c.fix and all_o_pp$mean_c.fix
## W = 1005.5, p-value = 0.0005747
## alternative hypothesis: true location shift is not equal to 0
##
##
## Wilcoxon rank sum exact test
##
## data: L_CHL_pp$mean_c.fix and H_CHL_pp$mean_c.fix
## W = 347, p-value = 3.686e-05
## alternative hypothesis: true location shift is not equal to 0
##
##
## Wilcoxon rank sum test with continuity correction
##
## data: L_CHL_pp$mean_chla and H_CHL_pp$mean_chla
## W = 305, p-value = 9.112e-06
## alternative hypothesis: true location shift is not equal to 0
## Alpha diversity
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/province_subsetting.R", encoding = "UTF-8")## salinity SST PO4_umol.l
## salinity 1.00000000 0.57540540 -0.6828060
## SST 0.57540540 1.00000000 -0.6302509
## PO4_umol.l -0.68280605 -0.63025085 1.0000000
## Si_umol.l -0.16830561 0.21170774 0.1432568
## NO3_umol.l -0.60194363 -0.58370559 0.9560053
## oxygen.umol.l. -0.66699610 -0.93734473 0.6531651
## distance_to_province_boundary.km. 0.11064621 0.42951074 -0.0878697
## Total.N..nmol.L. -0.48329642 -0.49266453 0.4549196
## Total.C..nmol.L. -0.47038064 -0.51942887 0.4290759
## chlorophyll -0.64615522 -0.53369153 0.5404505
## Distance_coast.km. -0.06131868 0.66631155 -0.1848614
## Shannon.auto.euk 0.58225737 0.61516489 -0.4785243
## Shannon.auto.cynao 0.05172859 0.03903127 -0.2174482
## Shannon.mixo 0.47777389 0.75039087 -0.4562699
## Shannon.het.euk 0.44801855 0.67512798 -0.4078585
## Shannon.het.prok 0.23353001 0.43438970 -0.3105365
## Si_umol.l NO3_umol.l oxygen.umol.l.
## salinity -0.16830561 -0.60194363 -0.66699610
## SST 0.21170774 -0.58370559 -0.93734473
## PO4_umol.l 0.14325676 0.95600527 0.65316510
## Si_umol.l 1.00000000 0.20017106 -0.09261576
## NO3_umol.l 0.20017106 1.00000000 0.62055758
## oxygen.umol.l. -0.09261576 0.62055758 1.00000000
## distance_to_province_boundary.km. 0.10664541 -0.01905593 -0.38936817
## Total.N..nmol.L. 0.02602950 0.36938122 0.58937772
## Total.C..nmol.L. 0.01338395 0.34130023 0.62726369
## chlorophyll -0.06754989 0.38165942 0.57112731
## Distance_coast.km. 0.30416880 -0.14808760 -0.60797051
## Shannon.auto.euk -0.07662397 -0.35429896 -0.65943334
## Shannon.auto.cynao -0.11810890 -0.24644504 -0.21949313
## Shannon.mixo 0.11746228 -0.39175783 -0.75896855
## Shannon.het.euk 0.01317759 -0.35512733 -0.76374596
## Shannon.het.prok -0.04567720 -0.30577210 -0.58265406
## distance_to_province_boundary.km.
## salinity 0.11064621
## SST 0.42951074
## PO4_umol.l -0.08786970
## Si_umol.l 0.10664541
## NO3_umol.l -0.01905593
## oxygen.umol.l. -0.38936817
## distance_to_province_boundary.km. 1.00000000
## Total.N..nmol.L. -0.33237931
## Total.C..nmol.L. -0.38563763
## chlorophyll -0.27485080
## Distance_coast.km. 0.59816766
## Shannon.auto.euk 0.33220665
## Shannon.auto.cynao 0.02877739
## Shannon.mixo 0.42199027
## Shannon.het.euk 0.35577555
## Shannon.het.prok 0.28474645
## Total.N..nmol.L. Total.C..nmol.L. chlorophyll
## salinity -0.4832964 -0.47038064 -0.64615522
## SST -0.4926645 -0.51942887 -0.53369153
## PO4_umol.l 0.4549196 0.42907590 0.54045047
## Si_umol.l 0.0260295 0.01338395 -0.06754989
## NO3_umol.l 0.3693812 0.34130023 0.38165942
## oxygen.umol.l. 0.5893777 0.62726369 0.57112731
## distance_to_province_boundary.km. -0.3323793 -0.38563763 -0.27485080
## Total.N..nmol.L. 1.0000000 0.98367406 0.70964936
## Total.C..nmol.L. 0.9836741 1.00000000 0.70400456
## chlorophyll 0.7096494 0.70400456 1.00000000
## Distance_coast.km. -0.3451064 -0.40730206 -0.16971854
## Shannon.auto.euk -0.7254985 -0.73780734 -0.63499079
## Shannon.auto.cynao -0.1786156 -0.19810550 -0.03340140
## Shannon.mixo -0.5189190 -0.53318159 -0.46916558
## Shannon.het.euk -0.5165724 -0.56449922 -0.36488396
## Shannon.het.prok -0.3458171 -0.39159216 -0.19785706
## Distance_coast.km. Shannon.auto.euk
## salinity -0.06131868 0.582257369
## SST 0.66631155 0.615164890
## PO4_umol.l -0.18486137 -0.478524265
## Si_umol.l 0.30416880 -0.076623974
## NO3_umol.l -0.14808760 -0.354298957
## oxygen.umol.l. -0.60797051 -0.659433341
## distance_to_province_boundary.km. 0.59816766 0.332206655
## Total.N..nmol.L. -0.34510637 -0.725498521
## Total.C..nmol.L. -0.40730206 -0.737807344
## chlorophyll -0.16971854 -0.634990791
## Distance_coast.km. 1.00000000 0.407132887
## Shannon.auto.euk 0.40713289 1.000000000
## Shannon.auto.cynao 0.17403345 0.004737561
## Shannon.mixo 0.59904027 0.700528031
## Shannon.het.euk 0.63457042 0.615499035
## Shannon.het.prok 0.49826102 0.273295256
## Shannon.auto.cynao Shannon.mixo
## salinity 0.051728588 0.4777739
## SST 0.039031269 0.7503909
## PO4_umol.l -0.217448203 -0.4562699
## Si_umol.l -0.118108904 0.1174623
## NO3_umol.l -0.246445037 -0.3917578
## oxygen.umol.l. -0.219493132 -0.7589686
## distance_to_province_boundary.km. 0.028777391 0.4219903
## Total.N..nmol.L. -0.178615608 -0.5189190
## Total.C..nmol.L. -0.198105501 -0.5331816
## chlorophyll -0.033401395 -0.4691656
## Distance_coast.km. 0.174033450 0.5990403
## Shannon.auto.euk 0.004737561 0.7005280
## Shannon.auto.cynao 1.000000000 0.1439196
## Shannon.mixo 0.143919629 1.0000000
## Shannon.het.euk 0.358339486 0.7173753
## Shannon.het.prok 0.630939432 0.4288556
## Shannon.het.euk Shannon.het.prok
## salinity 0.44801855 0.2335300
## SST 0.67512798 0.4343897
## PO4_umol.l -0.40785855 -0.3105365
## Si_umol.l 0.01317759 -0.0456772
## NO3_umol.l -0.35512733 -0.3057721
## oxygen.umol.l. -0.76374596 -0.5826541
## distance_to_province_boundary.km. 0.35577555 0.2847465
## Total.N..nmol.L. -0.51657236 -0.3458171
## Total.C..nmol.L. -0.56449922 -0.3915922
## chlorophyll -0.36488396 -0.1978571
## Distance_coast.km. 0.63457042 0.4982610
## Shannon.auto.euk 0.61549903 0.2732953
## Shannon.auto.cynao 0.35833949 0.6309394
## Shannon.mixo 0.71737533 0.4288556
## Shannon.het.euk 1.00000000 0.6779220
## Shannon.het.prok 0.67792196 1.0000000## salinity SST PO4_umol.l
## salinity 1.00000000 0.9192503 -0.82939966
## SST 0.91925027 1.0000000 -0.85119075
## PO4_umol.l -0.82939966 -0.8511908 1.00000000
## Si_umol.l 0.08117764 0.3993385 -0.16365099
## NO3_umol.l -0.71843438 -0.8444573 0.93992052
## oxygen.umol.l. -0.90877023 -0.9738099 0.92325329
## distance_to_province_boundary.km. 0.29758069 0.2778384 0.06150449
## Total.N..nmol.L. -0.75304616 -0.8580825 0.58283905
## Total.C..nmol.L. -0.83189610 -0.8977495 0.66165365
## chlorophyll -0.27211693 -0.1557953 -0.17331604
## Distance_coast.km. 0.30731916 0.4334302 -0.05266322
## Shannon.auto.euk 0.75526928 0.8482848 -0.53977231
## Shannon.auto.cynao 0.89812260 0.8641590 -0.63308517
## Shannon.mixo 0.71352689 0.5596929 -0.54630729
## Shannon.het.euk 0.47122791 0.3054058 -0.50391604
## Shannon.het.prok 0.92384986 0.9257955 -0.68306963
## Si_umol.l NO3_umol.l oxygen.umol.l.
## salinity 0.08117764 -0.71843438 -0.90877023
## SST 0.39933849 -0.84445730 -0.97380993
## PO4_umol.l -0.16365099 0.93992052 0.92325329
## Si_umol.l 1.00000000 -0.30202836 -0.31530784
## NO3_umol.l -0.30202836 1.00000000 0.92719648
## oxygen.umol.l. -0.31530784 0.92719648 1.00000000
## distance_to_province_boundary.km. 0.05704953 -0.05037638 -0.23075426
## Total.N..nmol.L. -0.43173091 0.67816023 0.82070409
## Total.C..nmol.L. -0.33461459 0.73209726 0.87883388
## chlorophyll -0.05852504 -0.17148549 0.07823087
## Distance_coast.km. 0.19668400 -0.19324353 -0.33397633
## Shannon.auto.euk 0.33370326 -0.62756920 -0.79779539
## Shannon.auto.cynao 0.14439278 -0.63689357 -0.84965882
## Shannon.mixo -0.11484789 -0.45594197 -0.61023787
## Shannon.het.euk -0.41937714 -0.46784700 -0.45901150
## Shannon.het.prok 0.32849633 -0.61864836 -0.84704987
## distance_to_province_boundary.km.
## salinity 0.29758069
## SST 0.27783840
## PO4_umol.l 0.06150449
## Si_umol.l 0.05704953
## NO3_umol.l -0.05037638
## oxygen.umol.l. -0.23075426
## distance_to_province_boundary.km. 1.00000000
## Total.N..nmol.L. -0.50130387
## Total.C..nmol.L. -0.52804037
## chlorophyll -0.81403401
## Distance_coast.km. 0.30597715
## Shannon.auto.euk 0.69483769
## Shannon.auto.cynao 0.62820552
## Shannon.mixo 0.55648325
## Shannon.het.euk 0.30348090
## Shannon.het.prok 0.38494474
## Total.N..nmol.L. Total.C..nmol.L. chlorophyll
## salinity -0.7530462 -0.8318961 -0.27211693
## SST -0.8580825 -0.8977495 -0.15579526
## PO4_umol.l 0.5828390 0.6616537 -0.17331604
## Si_umol.l -0.4317309 -0.3346146 -0.05852504
## NO3_umol.l 0.6781602 0.7320973 -0.17148549
## oxygen.umol.l. 0.8207041 0.8788339 0.07823087
## distance_to_province_boundary.km. -0.5013039 -0.5280404 -0.81403401
## Total.N..nmol.L. 1.0000000 0.9855648 0.46505531
## Total.C..nmol.L. 0.9855648 1.0000000 0.44987456
## chlorophyll 0.4650553 0.4498746 1.00000000
## Distance_coast.km. -0.6760238 -0.6126381 -0.23095229
## Shannon.auto.euk -0.8368204 -0.8781902 -0.40861699
## Shannon.auto.cynao -0.8595447 -0.9238800 -0.49486658
## Shannon.mixo -0.3694825 -0.5039706 -0.37084771
## Shannon.het.euk -0.1304362 -0.2830640 -0.02197433
## Shannon.het.prok -0.8699942 -0.8916954 -0.42796606
## Distance_coast.km. Shannon.auto.euk
## salinity 0.30731916 0.7552693
## SST 0.43343019 0.8482848
## PO4_umol.l -0.05266322 -0.5397723
## Si_umol.l 0.19668400 0.3337033
## NO3_umol.l -0.19324353 -0.6275692
## oxygen.umol.l. -0.33397633 -0.7977954
## distance_to_province_boundary.km. 0.30597715 0.6948377
## Total.N..nmol.L. -0.67602378 -0.8368204
## Total.C..nmol.L. -0.61263813 -0.8781902
## chlorophyll -0.23095229 -0.4086170
## Distance_coast.km. 1.00000000 0.5473555
## Shannon.auto.euk 0.54735554 1.0000000
## Shannon.auto.cynao 0.47817209 0.9153357
## Shannon.mixo -0.16318239 0.6393873
## Shannon.het.euk -0.24898129 0.3639125
## Shannon.het.prok 0.48892435 0.8034138
## Shannon.auto.cynao Shannon.mixo
## salinity 0.8981226 0.7135269
## SST 0.8641590 0.5596929
## PO4_umol.l -0.6330852 -0.5463073
## Si_umol.l 0.1443928 -0.1148479
## NO3_umol.l -0.6368936 -0.4559420
## oxygen.umol.l. -0.8496588 -0.6102379
## distance_to_province_boundary.km. 0.6282055 0.5564833
## Total.N..nmol.L. -0.8595447 -0.3694825
## Total.C..nmol.L. -0.9238800 -0.5039706
## chlorophyll -0.4948666 -0.3708477
## Distance_coast.km. 0.4781721 -0.1631824
## Shannon.auto.euk 0.9153357 0.6393873
## Shannon.auto.cynao 1.0000000 0.7566961
## Shannon.mixo 0.7566961 1.0000000
## Shannon.het.euk 0.5163001 0.8288185
## Shannon.het.prok 0.8700087 0.5216297
## Shannon.het.euk Shannon.het.prok
## salinity 0.47122791 0.9238499
## SST 0.30540576 0.9257955
## PO4_umol.l -0.50391604 -0.6830696
## Si_umol.l -0.41937714 0.3284963
## NO3_umol.l -0.46784700 -0.6186484
## oxygen.umol.l. -0.45901150 -0.8470499
## distance_to_province_boundary.km. 0.30348090 0.3849447
## Total.N..nmol.L. -0.13043616 -0.8699942
## Total.C..nmol.L. -0.28306401 -0.8916954
## chlorophyll -0.02197433 -0.4279661
## Distance_coast.km. -0.24898129 0.4889243
## Shannon.auto.euk 0.36391245 0.8034138
## Shannon.auto.cynao 0.51630014 0.8700087
## Shannon.mixo 0.82881847 0.5216297
## Shannon.het.euk 1.00000000 0.1460287
## Shannon.het.prok 0.14602867 1.0000000## salinity SST PO4_umol.l
## salinity 1.00000000 0.73694375 -0.04892697
## SST 0.73694375 1.00000000 -0.16786816
## PO4_umol.l -0.04892697 -0.16786816 1.00000000
## Si_umol.l -0.05978916 0.01972349 0.17603325
## NO3_umol.l -0.09243063 -0.09547460 0.83194973
## oxygen.umol.l. -0.67483289 -0.80787136 0.16313056
## distance_to_province_boundary.km. -0.28678052 -0.64877062 0.07562858
## Total.N..nmol.L. -0.48589932 -0.70355201 0.21877027
## Total.C..nmol.L. -0.32758019 -0.46938977 0.27196502
## chlorophyll -0.53287105 -0.72545158 0.30087402
## Distance_coast.km. 0.01535381 -0.22251556 -0.05173560
## Shannon.auto.euk 0.55433528 0.78461214 -0.29755516
## Shannon.auto.cynao -0.70663477 -0.96641549 0.24770172
## Shannon.mixo 0.10108564 0.30160370 0.03095011
## Shannon.het.euk 0.01158799 0.25304383 -0.23892508
## Shannon.het.prok -0.21447862 -0.45829503 0.03033972
## Si_umol.l NO3_umol.l oxygen.umol.l.
## salinity -0.05978916 -0.09243063 -0.6748329
## SST 0.01972349 -0.09547460 -0.8078714
## PO4_umol.l 0.17603325 0.83194973 0.1631306
## Si_umol.l 1.00000000 0.55940105 0.1465304
## NO3_umol.l 0.55940105 1.00000000 0.1718969
## oxygen.umol.l. 0.14653035 0.17189695 1.0000000
## distance_to_province_boundary.km. -0.20739193 0.03731984 0.5012822
## Total.N..nmol.L. 0.20952334 0.09109798 0.5189096
## Total.C..nmol.L. 0.48347840 0.28776904 0.3925505
## chlorophyll -0.06368110 0.07985273 0.4041581
## Distance_coast.km. -0.33828267 -0.08897653 0.1094145
## Shannon.auto.euk -0.23920639 -0.28593443 -0.5685089
## Shannon.auto.cynao 0.01627567 0.12849507 0.7625627
## Shannon.mixo 0.15875293 0.12995180 -0.1082281
## Shannon.het.euk -0.44030047 -0.46904895 -0.2700368
## Shannon.het.prok 0.07698821 -0.11879331 0.2620854
## distance_to_province_boundary.km.
## salinity -0.28678052
## SST -0.64877062
## PO4_umol.l 0.07562858
## Si_umol.l -0.20739193
## NO3_umol.l 0.03731984
## oxygen.umol.l. 0.50128221
## distance_to_province_boundary.km. 1.00000000
## Total.N..nmol.L. 0.21590637
## Total.C..nmol.L. 0.09975904
## chlorophyll 0.21313490
## Distance_coast.km. 0.84990835
## Shannon.auto.euk -0.19746183
## Shannon.auto.cynao 0.52796374
## Shannon.mixo -0.18183453
## Shannon.het.euk -0.18207683
## Shannon.het.prok 0.05570925
## Total.N..nmol.L. Total.C..nmol.L. chlorophyll
## salinity -0.48589932 -0.32758019 -0.53287105
## SST -0.70355201 -0.46938977 -0.72545158
## PO4_umol.l 0.21877027 0.27196502 0.30087402
## Si_umol.l 0.20952334 0.48347840 -0.06368110
## NO3_umol.l 0.09109798 0.28776904 0.07985273
## oxygen.umol.l. 0.51890964 0.39255048 0.40415806
## distance_to_province_boundary.km. 0.21590637 0.09975904 0.21313490
## Total.N..nmol.L. 1.00000000 0.89376939 0.78589631
## Total.C..nmol.L. 0.89376939 1.00000000 0.53997347
## chlorophyll 0.78589631 0.53997347 1.00000000
## Distance_coast.km. -0.14933504 -0.20190748 -0.06119686
## Shannon.auto.euk -0.78815425 -0.61864205 -0.72434017
## Shannon.auto.cynao 0.79598648 0.56862957 0.81977693
## Shannon.mixo -0.59155240 -0.43917973 -0.50361748
## Shannon.het.euk -0.26215958 -0.38480603 0.07888226
## Shannon.het.prok 0.53867468 0.44001903 0.44399221
## Distance_coast.km. Shannon.auto.euk
## salinity 0.01535381 0.5543353
## SST -0.22251556 0.7846121
## PO4_umol.l -0.05173560 -0.2975552
## Si_umol.l -0.33828267 -0.2392064
## NO3_umol.l -0.08897653 -0.2859344
## oxygen.umol.l. 0.10941445 -0.5685089
## distance_to_province_boundary.km. 0.84990835 -0.1974618
## Total.N..nmol.L. -0.14933504 -0.7881543
## Total.C..nmol.L. -0.20190748 -0.6186421
## chlorophyll -0.06119686 -0.7243402
## Distance_coast.km. 1.00000000 0.2866082
## Shannon.auto.euk 0.28660815 1.0000000
## Shannon.auto.cynao 0.08552209 -0.8310338
## Shannon.mixo -0.13668206 0.3949155
## Shannon.het.euk 0.04971518 0.4560939
## Shannon.het.prok -0.23796127 -0.4941537
## Shannon.auto.cynao Shannon.mixo
## salinity -0.70663477 0.101085644
## SST -0.96641549 0.301603705
## PO4_umol.l 0.24770172 0.030950110
## Si_umol.l 0.01627567 0.158752935
## NO3_umol.l 0.12849507 0.129951805
## oxygen.umol.l. 0.76256271 -0.108228149
## distance_to_province_boundary.km. 0.52796374 -0.181834527
## Total.N..nmol.L. 0.79598648 -0.591552396
## Total.C..nmol.L. 0.56862957 -0.439179729
## chlorophyll 0.81977693 -0.503617476
## Distance_coast.km. 0.08552209 -0.136682056
## Shannon.auto.euk -0.83103376 0.394915498
## Shannon.auto.cynao 1.00000000 -0.330536579
## Shannon.mixo -0.33053658 1.000000000
## Shannon.het.euk -0.14894491 0.151401664
## Shannon.het.prok 0.57829950 -0.009566115
## Shannon.het.euk Shannon.het.prok
## salinity 0.01158799 -0.214478618
## SST 0.25304383 -0.458295034
## PO4_umol.l -0.23892508 0.030339720
## Si_umol.l -0.44030047 0.076988210
## NO3_umol.l -0.46904895 -0.118793308
## oxygen.umol.l. -0.27003683 0.262085369
## distance_to_province_boundary.km. -0.18207683 0.055709245
## Total.N..nmol.L. -0.26215958 0.538674678
## Total.C..nmol.L. -0.38480603 0.440019033
## chlorophyll 0.07888226 0.443992213
## Distance_coast.km. 0.04971518 -0.237961268
## Shannon.auto.euk 0.45609388 -0.494153664
## Shannon.auto.cynao -0.14894491 0.578299505
## Shannon.mixo 0.15140166 -0.009566115
## Shannon.het.euk 1.00000000 0.046046518
## Shannon.het.prok 0.04604652 1.000000000## salinity SST PO4_umol.l
## salinity 1.000000000 0.87920668 0.314468820
## SST 0.879206680 1.00000000 0.380796585
## PO4_umol.l 0.314468820 0.38079659 1.000000000
## Si_umol.l -0.644386205 -0.41951843 0.202465861
## NO3_umol.l 0.092247932 0.08918181 0.149267895
## oxygen.umol.l. -0.788654154 -0.91343452 -0.351109211
## distance_to_province_boundary.km. 0.531137392 0.74349898 0.154564190
## Total.N..nmol.L. 0.009897566 0.13025519 0.241510074
## Total.C..nmol.L. -0.418119044 -0.31684252 0.045087467
## chlorophyll -0.099727016 -0.08581525 -0.387357688
## Distance_coast.km. 0.222930838 0.20672528 0.003665338
## Shannon.auto.euk 0.122246647 0.06823518 -0.388087702
## Shannon.auto.cynao 0.361771251 0.15739875 0.181565330
## Shannon.mixo -0.112569002 0.02400567 0.112779200
## Shannon.het.euk 0.053058750 0.15625827 -0.310248425
## Shannon.het.prok -0.254080205 -0.01209513 -0.205245521
## Si_umol.l NO3_umol.l oxygen.umol.l.
## salinity -0.64438620 0.09224793 -0.78865415
## SST -0.41951843 0.08918181 -0.91343452
## PO4_umol.l 0.20246586 0.14926789 -0.35110921
## Si_umol.l 1.00000000 -0.17521392 0.40443652
## NO3_umol.l -0.17521392 1.00000000 -0.12159374
## oxygen.umol.l. 0.40443652 -0.12159374 1.00000000
## distance_to_province_boundary.km. -0.47907356 0.15201029 -0.80992719
## Total.N..nmol.L. 0.15615767 -0.13236799 -0.07139755
## Total.C..nmol.L. 0.29800360 -0.02881342 0.37127307
## chlorophyll 0.18297775 -0.06329816 0.24702525
## Distance_coast.km. -0.51528026 0.31524389 -0.43697883
## Shannon.auto.euk -0.30401402 -0.23749216 -0.17607028
## Shannon.auto.cynao -0.22888145 0.03349113 0.15234378
## Shannon.mixo -0.09338216 -0.03713669 -0.14105719
## Shannon.het.euk -0.28110156 -0.13109056 -0.22211825
## Shannon.het.prok 0.50289931 -0.09986340 0.10713117
## distance_to_province_boundary.km.
## salinity 0.5311374
## SST 0.7434990
## PO4_umol.l 0.1545642
## Si_umol.l -0.4790736
## NO3_umol.l 0.1520103
## oxygen.umol.l. -0.8099272
## distance_to_province_boundary.km. 1.0000000
## Total.N..nmol.L. -0.1310535
## Total.C..nmol.L. -0.3293941
## chlorophyll -0.3927781
## Distance_coast.km. 0.6468723
## Shannon.auto.euk 0.2986157
## Shannon.auto.cynao -0.2426556
## Shannon.mixo 0.5242450
## Shannon.het.euk 0.4711185
## Shannon.het.prok -0.1944195
## Total.N..nmol.L. Total.C..nmol.L. chlorophyll
## salinity 0.009897566 -0.418119044 -0.09972702
## SST 0.130255188 -0.316842517 -0.08581525
## PO4_umol.l 0.241510074 0.045087467 -0.38735769
## Si_umol.l 0.156157667 0.298003597 0.18297775
## NO3_umol.l -0.132367989 -0.028813421 -0.06329816
## oxygen.umol.l. -0.071397551 0.371273072 0.24702525
## distance_to_province_boundary.km. -0.131053464 -0.329394081 -0.39277806
## Total.N..nmol.L. 1.000000000 0.800899586 0.37897454
## Total.C..nmol.L. 0.800899586 1.000000000 0.33680601
## chlorophyll 0.378974537 0.336806007 1.00000000
## Distance_coast.km. -0.370947852 -0.340377118 -0.62372987
## Shannon.auto.euk -0.279841572 -0.227069364 -0.16306070
## Shannon.auto.cynao 0.032627621 0.078543332 0.09939665
## Shannon.mixo -0.174703800 0.057965135 -0.59483544
## Shannon.het.euk -0.006708630 -0.003711595 0.23012908
## Shannon.het.prok 0.202685361 0.146287852 0.60801232
## Distance_coast.km. Shannon.auto.euk
## salinity 0.222930838 0.12224665
## SST 0.206725279 0.06823518
## PO4_umol.l 0.003665338 -0.38808770
## Si_umol.l -0.515280256 -0.30401402
## NO3_umol.l 0.315243889 -0.23749216
## oxygen.umol.l. -0.436978828 -0.17607028
## distance_to_province_boundary.km. 0.646872313 0.29861565
## Total.N..nmol.L. -0.370947852 -0.27984157
## Total.C..nmol.L. -0.340377118 -0.22706936
## chlorophyll -0.623729872 -0.16306070
## Distance_coast.km. 1.000000000 0.46093617
## Shannon.auto.euk 0.460936175 1.00000000
## Shannon.auto.cynao -0.330171835 -0.06913777
## Shannon.mixo 0.617842840 0.43257060
## Shannon.het.euk 0.363611030 0.43123865
## Shannon.het.prok -0.509648603 -0.33834419
## Shannon.auto.cynao Shannon.mixo
## salinity 0.36177125 -0.11256900
## SST 0.15739875 0.02400567
## PO4_umol.l 0.18156533 0.11277920
## Si_umol.l -0.22888145 -0.09338216
## NO3_umol.l 0.03349113 -0.03713669
## oxygen.umol.l. 0.15234378 -0.14105719
## distance_to_province_boundary.km. -0.24265558 0.52424496
## Total.N..nmol.L. 0.03262762 -0.17470380
## Total.C..nmol.L. 0.07854333 0.05796514
## chlorophyll 0.09939665 -0.59483544
## Distance_coast.km. -0.33017183 0.61784284
## Shannon.auto.euk -0.06913777 0.43257060
## Shannon.auto.cynao 1.00000000 -0.19622480
## Shannon.mixo -0.19622480 1.00000000
## Shannon.het.euk -0.32404429 0.38414736
## Shannon.het.prok -0.12226281 -0.48654072
## Shannon.het.euk Shannon.het.prok
## salinity 0.053058750 -0.25408020
## SST 0.156258268 -0.01209513
## PO4_umol.l -0.310248425 -0.20524552
## Si_umol.l -0.281101564 0.50289931
## NO3_umol.l -0.131090557 -0.09986340
## oxygen.umol.l. -0.222118249 0.10713117
## distance_to_province_boundary.km. 0.471118488 -0.19441955
## Total.N..nmol.L. -0.006708630 0.20268536
## Total.C..nmol.L. -0.003711595 0.14628785
## chlorophyll 0.230129084 0.60801232
## Distance_coast.km. 0.363611030 -0.50964860
## Shannon.auto.euk 0.431238653 -0.33834419
## Shannon.auto.cynao -0.324044285 -0.12226281
## Shannon.mixo 0.384147356 -0.48654072
## Shannon.het.euk 1.000000000 0.09656213
## Shannon.het.prok 0.096562134 1.00000000## salinity SST PO4_umol.l
## salinity 1.00000000 -0.71809346 -0.70151225
## SST -0.71809346 1.00000000 0.17336786
## PO4_umol.l -0.70151225 0.17336786 1.00000000
## Si_umol.l 0.78044963 -0.30147132 -0.94433821
## NO3_umol.l 0.12592409 0.11092964 -0.27566435
## oxygen.umol.l. -0.07468744 0.34450008 -0.34254348
## distance_to_province_boundary.km. -0.08344985 0.17519046 -0.41890359
## Total.N..nmol.L. -0.33846056 -0.10626472 0.34699175
## Total.C..nmol.L. -0.29859842 -0.10041545 0.60421306
## chlorophyll -0.73397189 0.53074611 0.37754599
## Distance_coast.km. -0.35434962 0.41544450 -0.21363493
## Shannon.auto.euk -0.33639342 0.40746933 0.37348355
## Shannon.auto.cynao 0.07510064 -0.51225594 0.07962103
## Shannon.mixo 0.20453301 -0.39888507 0.01247210
## Shannon.het.euk 0.57775784 -0.65980880 -0.34748782
## Shannon.het.prok 0.13640992 -0.02302651 -0.47915183
## Si_umol.l NO3_umol.l oxygen.umol.l.
## salinity 0.78044963 0.12592409 -0.074687437
## SST -0.30147132 0.11092964 0.344500084
## PO4_umol.l -0.94433821 -0.27566435 -0.342543484
## Si_umol.l 1.00000000 0.30542196 0.224258253
## NO3_umol.l 0.30542196 1.00000000 0.505616474
## oxygen.umol.l. 0.22425825 0.50561647 1.000000000
## distance_to_province_boundary.km. 0.31286132 0.24848259 0.741790874
## Total.N..nmol.L. -0.38198230 0.15883729 0.273083023
## Total.C..nmol.L. -0.59643144 0.20153034 -0.118379410
## chlorophyll -0.54202034 -0.24773002 0.034096678
## Distance_coast.km. 0.09190984 0.23453313 0.709615169
## Shannon.auto.euk -0.44396437 0.23682493 0.173556736
## Shannon.auto.cynao -0.06458927 -0.12872043 -0.005918699
## Shannon.mixo 0.04823606 -0.14689672 0.011860116
## Shannon.het.euk 0.32755636 0.15312032 0.285254302
## Shannon.het.prok 0.37436525 0.09654104 0.604145439
## distance_to_province_boundary.km.
## salinity -0.08344985
## SST 0.17519046
## PO4_umol.l -0.41890359
## Si_umol.l 0.31286132
## NO3_umol.l 0.24848259
## oxygen.umol.l. 0.74179087
## distance_to_province_boundary.km. 1.00000000
## Total.N..nmol.L. 0.22336779
## Total.C..nmol.L. -0.37760879
## chlorophyll 0.14569155
## Distance_coast.km. 0.94707556
## Shannon.auto.euk -0.35552386
## Shannon.auto.cynao 0.19094787
## Shannon.mixo 0.24429203
## Shannon.het.euk 0.31589743
## Shannon.het.prok 0.77287299
## Total.N..nmol.L. Total.C..nmol.L. chlorophyll
## salinity -0.33846056 -0.29859842 -0.73397189
## SST -0.10626472 -0.10041545 0.53074611
## PO4_umol.l 0.34699175 0.60421306 0.37754599
## Si_umol.l -0.38198230 -0.59643144 -0.54202034
## NO3_umol.l 0.15883729 0.20153034 -0.24773002
## oxygen.umol.l. 0.27308302 -0.11837941 0.03409668
## distance_to_province_boundary.km. 0.22336779 -0.37760879 0.14569155
## Total.N..nmol.L. 1.00000000 0.47062813 0.30170130
## Total.C..nmol.L. 0.47062813 1.00000000 -0.05087915
## chlorophyll 0.30170130 -0.05087915 1.00000000
## Distance_coast.km. 0.23582121 -0.32312346 0.34591446
## Shannon.auto.euk 0.08714721 0.44929501 0.27246051
## Shannon.auto.cynao 0.51641267 0.21922886 0.10907501
## Shannon.mixo 0.06552701 0.14295359 -0.39258423
## Shannon.het.euk 0.36970788 -0.05893713 -0.24728016
## Shannon.het.prok 0.10961583 -0.34370757 0.10281594
## Distance_coast.km. Shannon.auto.euk
## salinity -0.35434962 -0.33639342
## SST 0.41544450 0.40746933
## PO4_umol.l -0.21363493 0.37348355
## Si_umol.l 0.09190984 -0.44396437
## NO3_umol.l 0.23453313 0.23682493
## oxygen.umol.l. 0.70961517 0.17355674
## distance_to_province_boundary.km. 0.94707556 -0.35552386
## Total.N..nmol.L. 0.23582121 0.08714721
## Total.C..nmol.L. -0.32312346 0.44929501
## chlorophyll 0.34591446 0.27246051
## Distance_coast.km. 1.00000000 -0.22428275
## Shannon.auto.euk -0.22428275 1.00000000
## Shannon.auto.cynao 0.05465687 -0.15432448
## Shannon.mixo 0.09232689 -0.45016088
## Shannon.het.euk 0.10719402 -0.13050706
## Shannon.het.prok 0.62888829 -0.25228223
## Shannon.auto.cynao Shannon.mixo
## salinity 0.075100639 0.20453301
## SST -0.512255940 -0.39888507
## PO4_umol.l 0.079621032 0.01247210
## Si_umol.l -0.064589270 0.04823606
## NO3_umol.l -0.128720427 -0.14689672
## oxygen.umol.l. -0.005918699 0.01186012
## distance_to_province_boundary.km. 0.190947865 0.24429203
## Total.N..nmol.L. 0.516412672 0.06552701
## Total.C..nmol.L. 0.219228856 0.14295359
## chlorophyll 0.109075008 -0.39258423
## Distance_coast.km. 0.054656873 0.09232689
## Shannon.auto.euk -0.154324485 -0.45016088
## Shannon.auto.cynao 1.000000000 0.36663161
## Shannon.mixo 0.366631613 1.00000000
## Shannon.het.euk 0.419973466 0.27255803
## Shannon.het.prok 0.296902717 0.29497292
## Shannon.het.euk Shannon.het.prok
## salinity 0.57775784 0.13640992
## SST -0.65980880 -0.02302651
## PO4_umol.l -0.34748782 -0.47915183
## Si_umol.l 0.32755636 0.37436525
## NO3_umol.l 0.15312032 0.09654104
## oxygen.umol.l. 0.28525430 0.60414544
## distance_to_province_boundary.km. 0.31589743 0.77287299
## Total.N..nmol.L. 0.36970788 0.10961583
## Total.C..nmol.L. -0.05893713 -0.34370757
## chlorophyll -0.24728016 0.10281594
## Distance_coast.km. 0.10719402 0.62888829
## Shannon.auto.euk -0.13050706 -0.25228223
## Shannon.auto.cynao 0.41997347 0.29690272
## Shannon.mixo 0.27255803 0.29497292
## Shannon.het.euk 1.00000000 0.39522627
## Shannon.het.prok 0.39522627 1.00000000## salinity SST PO4_umol.l
## salinity 1.00000000 -0.61751121 -0.79331729
## SST -0.61751121 1.00000000 0.24882791
## PO4_umol.l -0.79331729 0.24882791 1.00000000
## Si_umol.l 0.11213391 -0.50196129 0.15156140
## NO3_umol.l -0.46815567 -0.19904066 0.83296152
## oxygen.umol.l. -0.04371799 -0.30226698 0.02864356
## distance_to_province_boundary.km. -0.62458259 0.27434618 0.70527422
## Total.N..nmol.L. -0.59382882 0.04283276 0.70869400
## Total.C..nmol.L. -0.57250097 0.03329655 0.66105820
## chlorophyll -0.67800291 0.08759356 0.74420785
## Distance_coast.km. -0.76321610 0.52376506 0.77153773
## Shannon.auto.euk 0.70166597 -0.55257100 -0.66065056
## Shannon.auto.cynao 0.63018309 -0.52975607 -0.67635615
## Shannon.mixo 0.34531292 -0.56899983 -0.30184730
## Shannon.het.euk 0.52034416 -0.14527922 -0.64337243
## Shannon.het.prok 0.03971981 0.31161930 -0.09834740
## Si_umol.l NO3_umol.l oxygen.umol.l.
## salinity 0.11213391 -0.46815567 -0.043717989
## SST -0.50196129 -0.19904066 -0.302266975
## PO4_umol.l 0.15156140 0.83296152 0.028643559
## Si_umol.l 1.00000000 0.57771852 0.393922579
## NO3_umol.l 0.57771852 1.00000000 0.257828081
## oxygen.umol.l. 0.39392258 0.25782808 1.000000000
## distance_to_province_boundary.km. -0.12402102 0.39418076 -0.176352516
## Total.N..nmol.L. 0.45725522 0.75736055 0.364746337
## Total.C..nmol.L. 0.46422318 0.72838524 0.510483088
## chlorophyll 0.26564284 0.72891716 0.422125278
## Distance_coast.km. -0.25245884 0.46003102 -0.094453949
## Shannon.auto.euk 0.13864126 -0.32480867 0.008191003
## Shannon.auto.cynao 0.05178447 -0.40027774 -0.119446440
## Shannon.mixo 0.18055465 0.01526297 0.531776829
## Shannon.het.euk -0.29667479 -0.54498027 -0.009492525
## Shannon.het.prok -0.56057071 -0.25587882 -0.433178651
## distance_to_province_boundary.km.
## salinity -0.6245826
## SST 0.2743462
## PO4_umol.l 0.7052742
## Si_umol.l -0.1240210
## NO3_umol.l 0.3941808
## oxygen.umol.l. -0.1763525
## distance_to_province_boundary.km. 1.0000000
## Total.N..nmol.L. 0.3442879
## Total.C..nmol.L. 0.3099963
## chlorophyll 0.3881561
## Distance_coast.km. 0.5966911
## Shannon.auto.euk -0.7046744
## Shannon.auto.cynao -0.6408806
## Shannon.mixo -0.4417136
## Shannon.het.euk -0.6666762
## Shannon.het.prok -0.1253249
## Total.N..nmol.L. Total.C..nmol.L. chlorophyll
## salinity -0.59382882 -0.57250097 -0.67800291
## SST 0.04283276 0.03329655 0.08759356
## PO4_umol.l 0.70869400 0.66105820 0.74420785
## Si_umol.l 0.45725522 0.46422318 0.26564284
## NO3_umol.l 0.75736055 0.72838524 0.72891716
## oxygen.umol.l. 0.36474634 0.51048309 0.42212528
## distance_to_province_boundary.km. 0.34428789 0.30999633 0.38815607
## Total.N..nmol.L. 1.00000000 0.97696292 0.86140528
## Total.C..nmol.L. 0.97696292 1.00000000 0.86399021
## chlorophyll 0.86140528 0.86399021 1.00000000
## Distance_coast.km. 0.51360323 0.49235325 0.62041803
## Shannon.auto.euk -0.40977982 -0.42022774 -0.48764606
## Shannon.auto.cynao -0.40731166 -0.42946707 -0.50757699
## Shannon.mixo 0.03853143 0.12726017 0.13314415
## Shannon.het.euk -0.42807049 -0.40123977 -0.35626694
## Shannon.het.prok -0.28929389 -0.35535504 -0.16790464
## Distance_coast.km. Shannon.auto.euk
## salinity -0.76321610 0.701665965
## SST 0.52376506 -0.552571001
## PO4_umol.l 0.77153773 -0.660650562
## Si_umol.l -0.25245884 0.138641261
## NO3_umol.l 0.46003102 -0.324808668
## oxygen.umol.l. -0.09445395 0.008191003
## distance_to_province_boundary.km. 0.59669110 -0.704674354
## Total.N..nmol.L. 0.51360323 -0.409779825
## Total.C..nmol.L. 0.49235325 -0.420227736
## chlorophyll 0.62041803 -0.487646059
## Distance_coast.km. 1.00000000 -0.788268279
## Shannon.auto.euk -0.78826828 1.000000000
## Shannon.auto.cynao -0.68676746 0.791413173
## Shannon.mixo -0.28950361 0.418627858
## Shannon.het.euk -0.50454707 0.597832648
## Shannon.het.prok 0.02910360 0.110597581
## Shannon.auto.cynao Shannon.mixo
## salinity 0.63018309 0.34531292
## SST -0.52975607 -0.56899983
## PO4_umol.l -0.67635615 -0.30184730
## Si_umol.l 0.05178447 0.18055465
## NO3_umol.l -0.40027774 0.01526297
## oxygen.umol.l. -0.11944644 0.53177683
## distance_to_province_boundary.km. -0.64088057 -0.44171357
## Total.N..nmol.L. -0.40731166 0.03853143
## Total.C..nmol.L. -0.42946707 0.12726017
## chlorophyll -0.50757699 0.13314415
## Distance_coast.km. -0.68676746 -0.28950361
## Shannon.auto.euk 0.79141317 0.41862786
## Shannon.auto.cynao 1.00000000 0.45520140
## Shannon.mixo 0.45520140 1.00000000
## Shannon.het.euk 0.56774931 0.43852811
## Shannon.het.prok 0.13669361 0.02025218
## Shannon.het.euk Shannon.het.prok
## salinity 0.520344159 0.03971981
## SST -0.145279219 0.31161930
## PO4_umol.l -0.643372432 -0.09834740
## Si_umol.l -0.296674786 -0.56057071
## NO3_umol.l -0.544980271 -0.25587882
## oxygen.umol.l. -0.009492525 -0.43317865
## distance_to_province_boundary.km. -0.666676198 -0.12532491
## Total.N..nmol.L. -0.428070486 -0.28929389
## Total.C..nmol.L. -0.401239775 -0.35535504
## chlorophyll -0.356266940 -0.16790464
## Distance_coast.km. -0.504547065 0.02910360
## Shannon.auto.euk 0.597832648 0.11059758
## Shannon.auto.cynao 0.567749308 0.13669361
## Shannon.mixo 0.438528111 0.02025218
## Shannon.het.euk 1.000000000 0.42838773
## Shannon.het.prok 0.428387727 1.00000000## salinity SST PO4_umol.l Si_umol.l
## salinity 1.0000000 0.8006039 0.85111572 0.90084207
## SST 0.8006039 1.0000000 0.72718338 0.66233423
## PO4_umol.l 0.8511157 0.7271834 1.00000000 0.93501319
## Si_umol.l 0.9008421 0.6623342 0.93501319 1.00000000
## NO3_umol.l 0.8199221 0.4337361 0.83691666 0.90588006
## oxygen.umol.l. -0.9021413 -0.6235597 -0.89690456 -0.94776936
## distance_to_province_boundary.km. 0.3759016 0.1634751 0.04706224 0.09863302
## Total.N..nmol.L. 0.4851783 0.2752179 0.56192570 0.56780994
## Total.C..nmol.L. 0.4949755 0.2576365 0.68930716 0.69358510
## chlorophyll 0.5515748 0.5599866 0.70184811 0.60418830
## Distance_coast.km. 0.1569345 -0.2798908 0.03061925 0.21635416
## Shannon.auto.euk -0.7910566 -0.6107202 -0.70857130 -0.68069058
## Shannon.auto.cynao 0.5082126 0.3035102 0.82721556 0.74353594
## Shannon.mixo 0.3654565 0.3997138 0.24658715 0.38017127
## Shannon.het.euk 0.6715591 0.3723823 0.64959176 0.81769295
## Shannon.het.prok 0.4593688 0.4933059 0.38879696 0.35364352
## NO3_umol.l oxygen.umol.l.
## salinity 0.8199221 -0.9021413
## SST 0.4337361 -0.6235597
## PO4_umol.l 0.8369167 -0.8969046
## Si_umol.l 0.9058801 -0.9477694
## NO3_umol.l 1.0000000 -0.9621941
## oxygen.umol.l. -0.9621941 1.0000000
## distance_to_province_boundary.km. 0.3145325 -0.2637861
## Total.N..nmol.L. 0.6988588 -0.7432613
## Total.C..nmol.L. 0.7802326 -0.7776962
## chlorophyll 0.3436086 -0.4485343
## Distance_coast.km. 0.5461440 -0.3794775
## Shannon.auto.euk -0.5407050 0.6113689
## Shannon.auto.cynao 0.6911338 -0.6792376
## Shannon.mixo 0.2596966 -0.3656410
## Shannon.het.euk 0.7458783 -0.8071523
## Shannon.het.prok 0.1272909 -0.1884333
## distance_to_province_boundary.km.
## salinity 0.37590161
## SST 0.16347508
## PO4_umol.l 0.04706224
## Si_umol.l 0.09863302
## NO3_umol.l 0.31453254
## oxygen.umol.l. -0.26378614
## distance_to_province_boundary.km. 1.00000000
## Total.N..nmol.L. -0.01877927
## Total.C..nmol.L. -0.15638848
## chlorophyll -0.41606776
## Distance_coast.km. 0.56166639
## Shannon.auto.euk -0.04649712
## Shannon.auto.cynao -0.30848567
## Shannon.mixo 0.22003514
## Shannon.het.euk -0.12427033
## Shannon.het.prok -0.01112767
## Total.N..nmol.L. Total.C..nmol.L. chlorophyll
## salinity 0.48517828 0.4949755 0.5515748
## SST 0.27521794 0.2576365 0.5599866
## PO4_umol.l 0.56192570 0.6893072 0.7018481
## Si_umol.l 0.56780994 0.6935851 0.6041883
## NO3_umol.l 0.69885875 0.7802326 0.3436086
## oxygen.umol.l. -0.74326130 -0.7776962 -0.4485343
## distance_to_province_boundary.km. -0.01877927 -0.1563885 -0.4160678
## Total.N..nmol.L. 1.00000000 0.8696267 0.2295206
## Total.C..nmol.L. 0.86962674 1.0000000 0.3525237
## chlorophyll 0.22952059 0.3525237 1.0000000
## Distance_coast.km. 0.36029516 0.3702985 -0.5593124
## Shannon.auto.euk -0.29537818 -0.3197065 -0.8535084
## Shannon.auto.cynao 0.55840862 0.7138745 0.7494067
## Shannon.mixo 0.12232566 0.1318082 -0.1536801
## Shannon.het.euk 0.72102923 0.7225493 0.4504882
## Shannon.het.prok -0.19157700 -0.1947412 0.5366129
## Distance_coast.km. Shannon.auto.euk
## salinity 0.15693451 -0.79105659
## SST -0.27989081 -0.61072021
## PO4_umol.l 0.03061925 -0.70857130
## Si_umol.l 0.21635416 -0.68069058
## NO3_umol.l 0.54614401 -0.54070498
## oxygen.umol.l. -0.37947750 0.61136885
## distance_to_province_boundary.km. 0.56166639 -0.04649712
## Total.N..nmol.L. 0.36029516 -0.29537818
## Total.C..nmol.L. 0.37029845 -0.31970647
## chlorophyll -0.55931242 -0.85350839
## Distance_coast.km. 1.00000000 0.25435110
## Shannon.auto.euk 0.25435110 1.00000000
## Shannon.auto.cynao -0.03672657 -0.60617737
## Shannon.mixo 0.22264019 0.12336389
## Shannon.het.euk 0.26478352 -0.48680805
## Shannon.het.prok -0.40698435 -0.60083585
## Shannon.auto.cynao Shannon.mixo
## salinity 0.50821265 0.3654565
## SST 0.30351021 0.3997138
## PO4_umol.l 0.82721556 0.2465871
## Si_umol.l 0.74353594 0.3801713
## NO3_umol.l 0.69113384 0.2596966
## oxygen.umol.l. -0.67923761 -0.3656410
## distance_to_province_boundary.km. -0.30848567 0.2200351
## Total.N..nmol.L. 0.55840862 0.1223257
## Total.C..nmol.L. 0.71387445 0.1318082
## chlorophyll 0.74940671 -0.1536801
## Distance_coast.km. -0.03672657 0.2226402
## Shannon.auto.euk -0.60617737 0.1233639
## Shannon.auto.cynao 1.00000000 -0.1359090
## Shannon.mixo -0.13590895 1.0000000
## Shannon.het.euk 0.60279672 0.4362018
## Shannon.het.prok 0.19274597 0.1854086
## Shannon.het.euk Shannon.het.prok
## salinity 0.6715591 0.45936885
## SST 0.3723823 0.49330586
## PO4_umol.l 0.6495918 0.38879696
## Si_umol.l 0.8176929 0.35364352
## NO3_umol.l 0.7458783 0.12729087
## oxygen.umol.l. -0.8071523 -0.18843330
## distance_to_province_boundary.km. -0.1242703 -0.01112767
## Total.N..nmol.L. 0.7210292 -0.19157700
## Total.C..nmol.L. 0.7225493 -0.19474119
## chlorophyll 0.4504882 0.53661290
## Distance_coast.km. 0.2647835 -0.40698435
## Shannon.auto.euk -0.4868080 -0.60083585
## Shannon.auto.cynao 0.6027967 0.19274597
## Shannon.mixo 0.4362018 0.18540855
## Shannon.het.euk 1.0000000 0.13545864
## Shannon.het.prok 0.1354586 1.00000000## salinity SST PO4_umol.l
## salinity 1.00000000 0.50735071 -0.1300205
## SST 0.50735071 1.00000000 0.3051762
## PO4_umol.l -0.13002050 0.30517624 1.0000000
## Si_umol.l -0.42700596 0.35606929 0.5446165
## NO3_umol.l -0.06616883 0.28638919 0.3752394
## oxygen.umol.l. -0.67493123 -0.42133998 0.4073784
## distance_to_province_boundary.km. 0.19038427 0.05160070 0.3154587
## Total.N..nmol.L. -0.27448249 -0.08022530 0.3171355
## Total.C..nmol.L. -0.29819600 0.07056475 0.3987944
## chlorophyll -0.71557158 -0.47908166 0.2085153
## Distance_coast.km. 0.58866279 0.78802565 0.2756108
## Shannon.auto.euk -0.08382627 -0.29919287 -0.2565724
## Shannon.auto.cynao -0.32094381 -0.13436747 0.3165222
## Shannon.mixo -0.04516231 -0.58794597 -0.3205543
## Shannon.het.euk -0.33440983 -0.50465938 -0.4576545
## Shannon.het.prok 0.24892857 -0.26870245 -0.5967856
## Si_umol.l NO3_umol.l oxygen.umol.l.
## salinity -0.42700596 -0.06616883 -0.67493123
## SST 0.35606929 0.28638919 -0.42133998
## PO4_umol.l 0.54461653 0.37523939 0.40737835
## Si_umol.l 1.00000000 0.27753455 0.11586495
## NO3_umol.l 0.27753455 1.00000000 0.29783164
## oxygen.umol.l. 0.11586495 0.29783164 1.00000000
## distance_to_province_boundary.km. -0.04729953 0.72576446 0.17918708
## Total.N..nmol.L. 0.09888521 0.17437001 0.54302848
## Total.C..nmol.L. 0.16123949 0.24927345 0.63657629
## chlorophyll 0.05151108 0.24518937 0.89452578
## Distance_coast.km. 0.22009260 0.45182022 -0.36709960
## Shannon.auto.euk -0.26858919 -0.31570464 -0.03594620
## Shannon.auto.cynao 0.02759324 0.54677937 0.72343669
## Shannon.mixo -0.67418712 -0.17459257 0.27188159
## Shannon.het.euk -0.35498501 -0.38147450 0.02698031
## Shannon.het.prok -0.28489403 -0.53259434 -0.58743720
## distance_to_province_boundary.km.
## salinity 0.19038427
## SST 0.05160070
## PO4_umol.l 0.31545868
## Si_umol.l -0.04729953
## NO3_umol.l 0.72576446
## oxygen.umol.l. 0.17918708
## distance_to_province_boundary.km. 1.00000000
## Total.N..nmol.L. 0.21187885
## Total.C..nmol.L. 0.23395082
## chlorophyll 0.20711218
## Distance_coast.km. 0.52905389
## Shannon.auto.euk -0.31125252
## Shannon.auto.cynao 0.65987743
## Shannon.mixo 0.02121727
## Shannon.het.euk -0.42675316
## Shannon.het.prok -0.29436966
## Total.N..nmol.L. Total.C..nmol.L. chlorophyll
## salinity -0.27448249 -0.29819600 -0.71557158
## SST -0.08022530 0.07056475 -0.47908166
## PO4_umol.l 0.31713547 0.39879444 0.20851530
## Si_umol.l 0.09888521 0.16123949 0.05151108
## NO3_umol.l 0.17437001 0.24927345 0.24518937
## oxygen.umol.l. 0.54302848 0.63657629 0.89452578
## distance_to_province_boundary.km. 0.21187885 0.23395082 0.20711218
## Total.N..nmol.L. 1.00000000 0.93899130 0.54161975
## Total.C..nmol.L. 0.93899130 1.00000000 0.61918870
## chlorophyll 0.54161975 0.61918870 1.00000000
## Distance_coast.km. 0.15951420 0.22845231 -0.38793855
## Shannon.auto.euk -0.66569970 -0.61422359 -0.08987988
## Shannon.auto.cynao 0.61365264 0.72435461 0.79894872
## Shannon.mixo -0.32620860 -0.30234181 0.29698647
## Shannon.het.euk -0.47536100 -0.47522607 0.17408134
## Shannon.het.prok -0.39112285 -0.59872400 -0.46920634
## Distance_coast.km. Shannon.auto.euk
## salinity 0.5886628 -0.08382627
## SST 0.7880256 -0.29919287
## PO4_umol.l 0.2756108 -0.25657236
## Si_umol.l 0.2200926 -0.26858919
## NO3_umol.l 0.4518202 -0.31570464
## oxygen.umol.l. -0.3670996 -0.03594620
## distance_to_province_boundary.km. 0.5290539 -0.31125252
## Total.N..nmol.L. 0.1595142 -0.66569970
## Total.C..nmol.L. 0.2284523 -0.61422359
## chlorophyll -0.3879386 -0.08987988
## Distance_coast.km. 1.0000000 -0.54698988
## Shannon.auto.euk -0.5469899 1.00000000
## Shannon.auto.cynao 0.1717332 -0.27844662
## Shannon.mixo -0.5935621 0.75436679
## Shannon.het.euk -0.7565213 0.68360808
## Shannon.het.prok -0.2041773 0.41366007
## Shannon.auto.cynao Shannon.mixo
## salinity -0.32094381 -0.04516231
## SST -0.13436747 -0.58794597
## PO4_umol.l 0.31652223 -0.32055427
## Si_umol.l 0.02759324 -0.67418712
## NO3_umol.l 0.54677937 -0.17459257
## oxygen.umol.l. 0.72343669 0.27188159
## distance_to_province_boundary.km. 0.65987743 0.02121727
## Total.N..nmol.L. 0.61365264 -0.32620860
## Total.C..nmol.L. 0.72435461 -0.30234181
## chlorophyll 0.79894872 0.29698647
## Distance_coast.km. 0.17173325 -0.59356214
## Shannon.auto.euk -0.27844662 0.75436679
## Shannon.auto.cynao 1.00000000 0.14697832
## Shannon.mixo 0.14697832 1.00000000
## Shannon.het.euk -0.25906313 0.64739384
## Shannon.het.prok -0.53814129 0.22997851
## Shannon.het.euk Shannon.het.prok
## salinity -0.33440983 0.2489286
## SST -0.50465938 -0.2687024
## PO4_umol.l -0.45765451 -0.5967856
## Si_umol.l -0.35498501 -0.2848940
## NO3_umol.l -0.38147450 -0.5325943
## oxygen.umol.l. 0.02698031 -0.5874372
## distance_to_province_boundary.km. -0.42675316 -0.2943697
## Total.N..nmol.L. -0.47536100 -0.3911228
## Total.C..nmol.L. -0.47522607 -0.5987240
## chlorophyll 0.17408134 -0.4692063
## Distance_coast.km. -0.75652126 -0.2041773
## Shannon.auto.euk 0.68360808 0.4136601
## Shannon.auto.cynao -0.25906313 -0.5381413
## Shannon.mixo 0.64739384 0.2299785
## Shannon.het.euk 1.00000000 0.4109484
## Shannon.het.prok 0.41094836 1.0000000## chlorophyll PPAVG specific_PP Shannon.auto.euk
## chlorophyll 1.0000000 0.4594386 -0.16190964 -0.65239347
## PPAVG 0.4594386 1.0000000 0.51069107 -0.65636323
## specific_PP -0.1619096 0.5106911 1.00000000 -0.13890292
## Shannon.auto.euk -0.6523935 -0.6563632 -0.13890292 1.00000000
## Shannon.auto.cynao -0.2053480 -0.1823733 -0.08449467 0.09241527
## Shannon.mixo -0.5061494 -0.3327072 0.12685245 0.72116138
## Shannon.het.euk -0.4138155 -0.3350151 0.09334712 0.70187062
## Shannon.het.prok -0.2606347 -0.1826148 0.03557413 0.41412157
## biomass_transport 0.6163046 -0.1772529 -0.48301775 -0.11904393
## Shannon.auto.cynao Shannon.mixo Shannon.het.euk
## chlorophyll -0.20534802 -0.5061494 -0.41381552
## PPAVG -0.18237333 -0.3327072 -0.33501514
## specific_PP -0.08449467 0.1268524 0.09334712
## Shannon.auto.euk 0.09241527 0.7211614 0.70187062
## Shannon.auto.cynao 1.00000000 0.2766513 0.35794835
## Shannon.mixo 0.27665132 1.0000000 0.79974669
## Shannon.het.euk 0.35794835 0.7997467 1.00000000
## Shannon.het.prok 0.62360656 0.4437247 0.65516983
## biomass_transport -0.02611334 -0.2381098 -0.08839877
## Shannon.het.prok biomass_transport
## chlorophyll -0.26063467 0.61630462
## PPAVG -0.18261481 -0.17725291
## specific_PP 0.03557413 -0.48301775
## Shannon.auto.euk 0.41412157 -0.11904393
## Shannon.auto.cynao 0.62360656 -0.02611334
## Shannon.mixo 0.44372467 -0.23810982
## Shannon.het.euk 0.65516983 -0.08839877
## Shannon.het.prok 1.00000000 0.06323802
## biomass_transport 0.06323802 1.00000000## chlorophyll PPAVG specific_PP Shannon.auto.euk
## chlorophyll 1.00000000 0.15769903 -0.3150017 -0.6914340
## PPAVG 0.15769903 1.00000000 0.8668742 -0.6143618
## specific_PP -0.31500171 0.86687424 1.0000000 -0.2904477
## Shannon.auto.euk -0.69143402 -0.61436185 -0.2904477 1.0000000
## Shannon.auto.cynao 0.97102328 0.16697948 -0.2797766 -0.7809692
## Shannon.mixo -0.21659787 -0.73192151 -0.6831985 0.4568567
## Shannon.het.euk 0.03499785 -0.41148161 -0.4204003 0.5804939
## Shannon.het.prok 0.73773529 -0.07372358 -0.5199886 -0.3402852
## biomass_transport -0.06521166 -0.67454539 -0.5571763 0.3511798
## Shannon.auto.cynao Shannon.mixo Shannon.het.euk
## chlorophyll 0.9710233 -0.2165979 0.03499785
## PPAVG 0.1669795 -0.7319215 -0.41148161
## specific_PP -0.2797766 -0.6831985 -0.42040034
## Shannon.auto.euk -0.7809692 0.4568567 0.58049393
## Shannon.auto.cynao 1.0000000 -0.2463451 -0.18295914
## Shannon.mixo -0.2463451 1.0000000 0.27492401
## Shannon.het.euk -0.1829591 0.2749240 1.00000000
## Shannon.het.prok 0.6443935 0.3800101 0.25625203
## biomass_transport -0.1292983 0.6114407 0.47671640
## Shannon.het.prok biomass_transport
## chlorophyll 0.73773529 -0.06521166
## PPAVG -0.07372358 -0.67454539
## specific_PP -0.51998859 -0.55717626
## Shannon.auto.euk -0.34028517 0.35117980
## Shannon.auto.cynao 0.64439350 -0.12929830
## Shannon.mixo 0.38001015 0.61144065
## Shannon.het.euk 0.25625203 0.47671640
## Shannon.het.prok 1.00000000 0.17626309
## biomass_transport 0.17626309 1.00000000## chlorophyll PPAVG specific_PP Shannon.auto.euk
## chlorophyll 1.00000000 0.85219172 0.4924962 -0.1531551
## PPAVG 0.85219172 1.00000000 0.8702918 -0.3003338
## specific_PP 0.49249616 0.87029178 1.0000000 -0.4550799
## Shannon.auto.euk -0.15315515 -0.30033382 -0.4550799 1.0000000
## Shannon.auto.cynao 0.35290235 0.48295858 0.5005788 -0.4800869
## Shannon.mixo -0.71878634 -0.53113253 -0.2575265 0.4343310
## Shannon.het.euk 0.06021807 -0.07173421 -0.2514529 0.5909971
## Shannon.het.prok 0.56092788 0.66260830 0.6042235 -0.2609766
## biomass_transport -0.27135741 -0.34064641 -0.3750232 0.2519177
## Shannon.auto.cynao Shannon.mixo Shannon.het.euk
## chlorophyll 0.35290235 -0.718786338 0.06021807
## PPAVG 0.48295858 -0.531132530 -0.07173421
## specific_PP 0.50057884 -0.257526534 -0.25145293
## Shannon.auto.euk -0.48008686 0.434331033 0.59099707
## Shannon.auto.cynao 1.00000000 -0.063429178 -0.53328545
## Shannon.mixo -0.06342918 1.000000000 0.20294516
## Shannon.het.euk -0.53328545 0.202945165 1.00000000
## Shannon.het.prok -0.01353832 -0.724491589 -0.29445086
## biomass_transport -0.50682372 -0.008327368 0.53613441
## Shannon.het.prok biomass_transport
## chlorophyll 0.56092788 -0.271357410
## PPAVG 0.66260830 -0.340646409
## specific_PP 0.60422354 -0.375023173
## Shannon.auto.euk -0.26097665 0.251917704
## Shannon.auto.cynao -0.01353832 -0.506823722
## Shannon.mixo -0.72449159 -0.008327368
## Shannon.het.euk -0.29445086 0.536134408
## Shannon.het.prok 1.00000000 -0.227013279
## biomass_transport -0.22701328 1.000000000## chlorophyll PPAVG specific_PP Shannon.auto.euk
## chlorophyll 1.00000000 0.03538157 -0.2217936 0.18643286
## PPAVG 0.03538157 1.00000000 0.9570629 -0.47249268
## specific_PP -0.22179360 0.95706289 1.0000000 -0.46479327
## Shannon.auto.euk 0.18643286 -0.47249268 -0.4647933 1.00000000
## Shannon.auto.cynao 0.52217115 0.28803241 0.2157468 -0.09783217
## Shannon.mixo -0.42831352 0.72627243 0.8098722 -0.54891155
## Shannon.het.euk -0.29520923 0.56976371 0.6933857 -0.22630610
## Shannon.het.prok 0.39460647 0.50611240 0.4121281 -0.09746624
## biomass_transport 0.83625924 -0.41650445 -0.6258140 0.29686101
## Shannon.auto.cynao Shannon.mixo Shannon.het.euk
## chlorophyll 0.52217115 -0.4283135 -0.2952092
## PPAVG 0.28803241 0.7262724 0.5697637
## specific_PP 0.21574678 0.8098722 0.6933857
## Shannon.auto.euk -0.09783217 -0.5489115 -0.2263061
## Shannon.auto.cynao 1.00000000 0.2179769 0.4931002
## Shannon.mixo 0.21797692 1.0000000 0.6209877
## Shannon.het.euk 0.49310016 0.6209877 1.0000000
## Shannon.het.prok 0.69819174 0.2069273 0.5121691
## biomass_transport 0.17066148 -0.7772132 -0.6809556
## Shannon.het.prok biomass_transport
## chlorophyll 0.39460647 0.83625924
## PPAVG 0.50611240 -0.41650445
## specific_PP 0.41212813 -0.62581400
## Shannon.auto.euk -0.09746624 0.29686101
## Shannon.auto.cynao 0.69819174 0.17066148
## Shannon.mixo 0.20692729 -0.77721320
## Shannon.het.euk 0.51216914 -0.68095561
## Shannon.het.prok 1.00000000 0.05160455
## biomass_transport 0.05160455 1.00000000## chlorophyll PPAVG specific_PP Shannon.auto.euk
## chlorophyll 1.00000000 0.7366228 -0.04608833 -0.09923484
## PPAVG 0.73662280 1.0000000 0.62607376 -0.45018404
## specific_PP -0.04608833 0.6260738 1.00000000 -0.61028807
## Shannon.auto.euk -0.09923484 -0.4501840 -0.61028807 1.00000000
## Shannon.auto.cynao -0.39234089 -0.7086496 -0.62886116 0.69823008
## Shannon.mixo 0.28688453 0.0793110 -0.28495508 0.53351781
## Shannon.het.euk -0.29191802 -0.2906215 -0.20351255 0.52641735
## Shannon.het.prok -0.02167886 -0.1865895 -0.25907062 0.25418398
## biomass_transport 0.08502448 -0.3377927 -0.59694345 0.45406412
## Shannon.auto.cynao Shannon.mixo Shannon.het.euk
## chlorophyll -0.3923409 0.2868845 -0.29191802
## PPAVG -0.7086496 0.0793110 -0.29062147
## specific_PP -0.6288612 -0.2849551 -0.20351255
## Shannon.auto.euk 0.6982301 0.5335178 0.52641735
## Shannon.auto.cynao 1.0000000 0.3146896 0.41182688
## Shannon.mixo 0.3146896 1.0000000 0.39112846
## Shannon.het.euk 0.4118269 0.3911285 1.00000000
## Shannon.het.prok 0.3657107 0.1154261 0.47925100
## biomass_transport 0.5659768 0.4631646 0.05831986
## Shannon.het.prok biomass_transport
## chlorophyll -0.02167886 0.08502448
## PPAVG -0.18658950 -0.33779271
## specific_PP -0.25907062 -0.59694345
## Shannon.auto.euk 0.25418398 0.45406412
## Shannon.auto.cynao 0.36571066 0.56597684
## Shannon.mixo 0.11542610 0.46316460
## Shannon.het.euk 0.47925100 0.05831986
## Shannon.het.prok 1.00000000 0.40266513
## biomass_transport 0.40266513 1.00000000## chlorophyll PPAVG specific_PP Shannon.auto.euk
## chlorophyll 1.000000000 0.7004835 0.32146445 0.02942925
## PPAVG 0.700483476 1.0000000 0.84506011 -0.39507524
## specific_PP 0.321464447 0.8450601 1.00000000 -0.76211677
## Shannon.auto.euk 0.029429248 -0.3950752 -0.76211677 1.00000000
## Shannon.auto.cynao 0.941699253 0.4397243 0.08425641 0.12808273
## Shannon.mixo 0.007300381 -0.4737569 -0.81350555 0.76555190
## Shannon.het.euk 0.457663934 -0.1456583 -0.49605847 0.67704213
## Shannon.het.prok -0.291822423 -0.7214593 -0.60076963 0.21421391
## biomass_transport 0.346207451 -0.1356339 -0.20102259 0.06860904
## Shannon.auto.cynao Shannon.mixo Shannon.het.euk
## chlorophyll 0.94169925 0.007300381 0.45766393
## PPAVG 0.43972428 -0.473756899 -0.14565832
## specific_PP 0.08425641 -0.813505554 -0.49605847
## Shannon.auto.euk 0.12808273 0.765551898 0.67704213
## Shannon.auto.cynao 1.00000000 0.134148617 0.62401336
## Shannon.mixo 0.13414862 1.000000000 0.68409085
## Shannon.het.euk 0.62401336 0.684090849 1.00000000
## Shannon.het.prok -0.01506632 0.071168352 0.06296718
## biomass_transport 0.53231698 -0.147236225 0.15060139
## Shannon.het.prok biomass_transport
## chlorophyll -0.29182242 0.34620745
## PPAVG -0.72145930 -0.13563391
## specific_PP -0.60076963 -0.20102259
## Shannon.auto.euk 0.21421391 0.06860904
## Shannon.auto.cynao -0.01506632 0.53231698
## Shannon.mixo 0.07116835 -0.14723622
## Shannon.het.euk 0.06296718 0.15060139
## Shannon.het.prok 1.00000000 0.76598091
## biomass_transport 0.76598091 1.00000000
## Call:corr.test(x = list_meta$meta_functions.z[A], y = list_meta$meta_functions.z$SST,
## method = "pearson", adjust = "holm")
## Correlation matrix
## [,1]
## Shannon.auto.euk 0.62
## Shannon.mixo 0.75
## Shannon.het.prok 0.43
## Sample Size
## [1] 121
## Probability values adjusted for multiple tests.
## [,1]
## Shannon.auto.euk 0
## Shannon.mixo 0
## Shannon.het.prok 0
##
## To see confidence intervals of the correlations, print with the short=FALSE option
## Call:corr.test(x = list_meta$meta_functions.z[B], y = list_meta$meta_functions.z[D],
## method = "pearson", adjust = "holm")
## Correlation matrix
## PO4_umol.l NO3_umol.l Total.N..nmol.L. Total.C..nmol.L.
## Shannon.auto.euk -0.48 -0.35 -0.73 -0.74
## Shannon.het.prok -0.31 -0.31 -0.35 -0.39
## chlorophyll
## Shannon.auto.euk -0.63
## Shannon.het.prok -0.20
## Sample Size
## [1] 121
## Probability values adjusted for multiple tests.
## PO4_umol.l NO3_umol.l Total.N..nmol.L. Total.C..nmol.L.
## Shannon.auto.euk 0 0 0 0
## Shannon.het.prok 0 0 0 0
## chlorophyll
## Shannon.auto.euk 0.00
## Shannon.het.prok 0.03
##
## To see confidence intervals of the correlations, print with the short=FALSE option
## Call:corr.test(x = list_meta$meta_functions.z$TotalCell.Count, y = list_meta$meta_functions.z[E],
## method = "pearson", adjust = "holm")
## Correlation matrix
## chlorophyll PPAVG
## [1,] 0.14 0.17
## Sample Size
## PPAVG
## [1,] 115 57
## Probability values adjusted for multiple tests.
## chlorophyll PPAVG
## [1,] 0.25 0.25
##
## To see confidence intervals of the correlations, print with the short=FALSE option
## Call:corr.test(x = meta_NAST[C], y = meta_NAST$PO4_umol.l, method = "pearson",
## adjust = "holm")
## Correlation matrix
## [,1]
## Shannon.auto.cynao 0.83
## Shannon.het.prok 0.39
## Sample Size
## [1] 10
## Probability values adjusted for multiple tests.
## [,1]
## Shannon.auto.cynao 0.01
## Shannon.het.prok 0.27
##
## To see confidence intervals of the correlations, print with the short=FALSE option
##
## Pearson's product-moment correlation
##
## data: meta_SATL_cold$Total.N..nmol.L. and meta_SATL_cold$Shannon.auto.cynao
## t = 4.7413, df = 13, p-value = 0.0003854
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.4790641 0.9293165
## sample estimates:
## cor
## 0.7959865##
## Pearson's product-moment correlation
##
## data: meta_BRAZ$Shannon.auto.euk and meta_BRAZ$SST
## t = 3.9239, df = 6, p-value = 0.007767
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.3570333 0.9719573
## sample estimates:
## cor
## 0.8482848
##
##
## Pearson's product-moment correlation
##
## data: meta_SATL_hot$Shannon.auto.euk and meta_SATL_hot$SST
## t = 0.29017, df = 18, p-value = 0.775
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.3859392 0.4957855
## sample estimates:
## cor
## 0.06823518##
## Pearson's product-moment correlation
##
## data: meta_BRAZ$Shannon.auto.euk and meta_BRAZ$Shannon.auto.cynao
## t = 5.5678, df = 6, p-value = 0.001422
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.5934368 0.9848003
## sample estimates:
## cor
## 0.9153357
##
##
## Pearson's product-moment correlation
##
## data: meta_SATL_cold$Shannon.auto.euk and meta_SATL_cold$Shannon.mixo
## t = 1.5499, df = 13, p-value = 0.1452
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1471072 0.7545354
## sample estimates:
## cor
## 0.3949155
##
##
## Pearson's product-moment correlation
##
## data: meta_CNRY$Shannon.auto.euk and meta_CNRY$Shannon.mixo
## t = 2.2583, df = 24, p-value = 0.0333
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.03732906 0.69352099
## sample estimates:
## cor
## 0.4186279
##
##
## Pearson's product-moment correlation
##
## data: meta_NADR$Shannon.auto.euk and meta_NADR$Shannon.mixo
## t = 3.8113, df = 11, p-value = 0.002886
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.3480444 0.9220900
## sample estimates:
## cor
## 0.7543668## Warning in rm(f, g, h, i, j, k): object 'f' not found## Warning in rm(f, g, h, i, j, k): object 'g' not found## Call:corr.test(x = list_meta$meta_auto_euk.z[test_env], y = list_meta$meta_auto_euk.z$Shannon,
## method = "pearson", adjust = "holm")
## Correlation matrix
## [,1]
## salinity 0.57
## SST 0.61
## PO4_umol.l -0.46
## Si_umol.l -0.05
## NO3_umol.l -0.34
## oxygen.umol.l. -0.66
## Total.N..nmol.L. -0.72
## Total.C..nmol.L. -0.73
## chlorophyll -0.62
## Sample Size
## [1] 129
## Probability values adjusted for multiple tests.
## [,1]
## salinity 0.00
## SST 0.00
## PO4_umol.l 0.00
## Si_umol.l 0.54
## NO3_umol.l 0.00
## oxygen.umol.l. 0.00
## Total.N..nmol.L. 0.00
## Total.C..nmol.L. 0.00
## chlorophyll 0.00
##
## To see confidence intervals of the correlations, print with the short=FALSE option
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_auto_euk.PP.z$PPAVG and list_meta$meta_auto_euk.PP.z$Shannon
## t = -6.2069, df = 57, p-value = 6.576e-08
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.7664903 -0.4525805
## sample estimates:
## cor
## -0.6350606
##
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_auto_euk.PP.z$specific_PP and list_meta$meta_auto_euk.PP.z$Shannon
## t = -1.4545, df = 57, p-value = 0.1513
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.42467962 0.07031858
## sample estimates:
## cor
## -0.1891701
##
## Call:corr.test(x = list_meta$meta_auto_cyano.z[test_env], y = list_meta$meta_auto_cyano.z$Shannon,
## method = "pearson", adjust = "holm")
## Correlation matrix
## [,1]
## salinity 0.05
## SST 0.06
## PO4_umol.l -0.20
## Si_umol.l -0.10
## NO3_umol.l -0.23
## oxygen.umol.l. -0.23
## Total.N..nmol.L. -0.17
## Total.C..nmol.L. -0.19
## chlorophyll -0.03
## Sample Size
## [1] 124
## Probability values adjusted for multiple tests.
## [,1]
## salinity 1.00
## SST 1.00
## PO4_umol.l 0.17
## Si_umol.l 1.00
## NO3_umol.l 0.08
## oxygen.umol.l. 0.08
## Total.N..nmol.L. 0.33
## Total.C..nmol.L. 0.21
## chlorophyll 1.00
##
## To see confidence intervals of the correlations, print with the short=FALSE option
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_auto_cyano.PP.z$PPAVG and list_meta$meta_auto_cyano.PP.z$Shannon
## t = -1.2428, df = 56, p-value = 0.2191
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.40498659 0.09864161
## sample estimates:
## cor
## -0.1638283
##
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_auto_cyano.PP.z$specific_PP and list_meta$meta_auto_cyano.PP.z$Shannon
## t = -0.46323, df = 56, p-value = 0.645
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.3150516 0.1996991
## sample estimates:
## cor
## -0.06178355
##
## Call:corr.test(x = list_meta$meta_mixo.z[test_env], y = list_meta$meta_mixo.z$Shannon,
## method = "pearson", adjust = "holm")
## Correlation matrix
## [,1]
## salinity 0.46
## SST 0.75
## PO4_umol.l -0.43
## Si_umol.l 0.12
## NO3_umol.l -0.37
## oxygen.umol.l. -0.75
## Total.N..nmol.L. -0.50
## Total.C..nmol.L. -0.52
## chlorophyll -0.44
## Sample Size
## [1] 129
## Probability values adjusted for multiple tests.
## [,1]
## salinity 0.00
## SST 0.00
## PO4_umol.l 0.00
## Si_umol.l 0.16
## NO3_umol.l 0.00
## oxygen.umol.l. 0.00
## Total.N..nmol.L. 0.00
## Total.C..nmol.L. 0.00
## chlorophyll 0.00
##
## To see confidence intervals of the correlations, print with the short=FALSE option
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_mixo.PP.z$PPAVG and list_meta$meta_mixo.PP.z$Shannon
## t = -2.0757, df = 57, p-value = 0.04244
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.488047041 -0.009670832
## sample estimates:
## cor
## -0.2650966
##
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_mixo.PP.z$specific_PP and list_meta$meta_mixo.PP.z$Shannon
## t = 1.0949, df = 57, p-value = 0.2782
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1168556 0.3854377
## sample estimates:
## cor
## 0.1435215
##
## Call:corr.test(x = list_meta$meta_het_euk.z[test_env], y = list_meta$meta_het_euk.z$Shannon,
## method = "pearson", adjust = "holm")
## Correlation matrix
## [,1]
## salinity 0.44
## SST 0.68
## PO4_umol.l -0.38
## Si_umol.l 0.03
## NO3_umol.l -0.33
## oxygen.umol.l. -0.76
## Total.N..nmol.L. -0.50
## Total.C..nmol.L. -0.55
## chlorophyll -0.35
## Sample Size
## [1] 129
## Probability values adjusted for multiple tests.
## [,1]
## salinity 0.00
## SST 0.00
## PO4_umol.l 0.00
## Si_umol.l 0.75
## NO3_umol.l 0.00
## oxygen.umol.l. 0.00
## Total.N..nmol.L. 0.00
## Total.C..nmol.L. 0.00
## chlorophyll 0.00
##
## To see confidence intervals of the correlations, print with the short=FALSE option
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_het_euk.PP.z$PPAVG and list_meta$meta_het_euk.PP.z$Shannon
## t = -2.1659, df = 57, p-value = 0.03452
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.49675624 -0.02116486
## sample estimates:
## cor
## -0.2757526
##
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_het_euk.PP.z$specific_PP and list_meta$meta_het_euk.PP.z$Shannon
## t = 0.66389, df = 57, p-value = 0.5094
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1723524 0.3361381
## sample estimates:
## cor
## 0.08759601
##
## Call:corr.test(x = list_meta$meta_het_prok.z[test_env], y = list_meta$meta_het_prok.z$Shannon,
## method = "pearson", adjust = "holm")
## Correlation matrix
## [,1]
## salinity 0.24
## SST 0.45
## PO4_umol.l -0.29
## Si_umol.l -0.02
## NO3_umol.l -0.29
## oxygen.umol.l. -0.59
## Total.N..nmol.L. -0.31
## Total.C..nmol.L. -0.36
## chlorophyll -0.18
## Sample Size
## [1] 124
## Probability values adjusted for multiple tests.
## [,1]
## salinity 0.03
## SST 0.00
## PO4_umol.l 0.00
## Si_umol.l 0.80
## NO3_umol.l 0.00
## oxygen.umol.l. 0.00
## Total.N..nmol.L. 0.00
## Total.C..nmol.L. 0.00
## chlorophyll 0.10
##
## To see confidence intervals of the correlations, print with the short=FALSE option
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_het_prok.PP.z$PPAVG and list_meta$meta_het_prok.PP.z$Shannon
## t = -1.0771, df = 56, p-value = 0.2861
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.3865323 0.1202614
## sample estimates:
## cor
## -0.1424596
##
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_het_prok.PP.z$specific_PP and list_meta$meta_het_prok.PP.z$Shannon
## t = 0.16961, df = 56, p-value = 0.8659
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2370235 0.2793205
## sample estimates:
## cor
## 0.02265958
##
## Call:corr.test(x = list_meta$meta_functions.z[test_env], y = list_meta$meta_functions.z$TotalCell.Count,
## method = "pearson", adjust = "holm")
## Correlation matrix
## [,1]
## salinity -0.10
## SST -0.08
## PO4_umol.l 0.01
## Si_umol.l 0.00
## NO3_umol.l -0.02
## oxygen.umol.l. 0.05
## Total.N..nmol.L. 0.20
## Total.C..nmol.L. 0.20
## chlorophyll 0.14
## Sample Size
## [1] 115
## Probability values adjusted for multiple tests.
## [,1]
## salinity 1.00
## SST 1.00
## PO4_umol.l 1.00
## Si_umol.l 1.00
## NO3_umol.l 1.00
## oxygen.umol.l. 1.00
## Total.N..nmol.L. 0.29
## Total.C..nmol.L. 0.29
## chlorophyll 0.89
##
## To see confidence intervals of the correlations, print with the short=FALSE option
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_functions.PP.z$PPAVG and list_meta$meta_functions.PP.z$TotalCell.Count
## t = 1.2673, df = 55, p-value = 0.2104
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.09635779 0.41096930
## sample estimates:
## cor
## 0.168439
##
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_functions.PP.z$specific_PP and list_meta$meta_functions.PP.z$TotalCell.Count
## t = 0.0059818, df = 55, p-value = 0.9952
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.2598157 0.2613193
## sample estimates:
## cor
## 0.0008065903
##
##
## Pearson's product-moment correlation
##
## data: meta_CNRY$PPAVG and meta_CNRY$Shannon.auto.euk
## t = -2.2693, df = 12, p-value = 0.04249
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.83560745 -0.02452912
## sample estimates:
## cor
## -0.5479769
##
##
## Pearson's product-moment correlation
##
## data: meta_CNRY$PPAVG and meta_CNRY$Shannon.auto.cynao
## t = -2.9066, df = 12, p-value = 0.01316
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.8749555 -0.1702580
## sample estimates:
## cor
## -0.6427724
##
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_functions.PP.z$PPAVG and list_meta$meta_functions.PP.z$TotalCell.Count
## t = 1.2673, df = 55, p-value = 0.2104
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.09635779 0.41096930
## sample estimates:
## cor
## 0.168439
##
##
## Pearson's product-moment correlation
##
## data: list_meta$meta_functions.PP.z$chlorophyll and list_meta$meta_functions.PP.z$TotalCell.Count
## t = 0.55893, df = 55, p-value = 0.5785
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1891185 0.3292722
## sample estimates:
## cor
## 0.0751525
wilcoxon test
require("ggpubr")## Loading required package: ggpubrL_CHL_mixo <- list_meta$meta_mixo%>%dplyr::filter(province %in% L_CHL)
H_CHL_mixo <- list_meta$meta_mixo%>%dplyr::filter(province %in% H_CHL)
print(wilcox.test(L_CHL_mixo$Shannon, H_CHL_mixo$Shannon, var.equal = TRUE))##
## Wilcoxon rank sum test with continuity correction
##
## data: L_CHL_mixo$Shannon and H_CHL_mixo$Shannon
## W = 3838, p-value < 2.2e-16
## alternative hypothesis: true location shift is not equal to 0## Warning: Removed 3 rows containing missing values (geom_point).
## Warning: Removed 3 rows containing missing values (geom_point).
## Warning: Removed 3 rows containing missing values (geom_point).
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/general_metadata_analysis.R", encoding = "UTF-8")
#define the import data
meta_sub <- c("Site","province", "SST", "salinity", "distance_to_province_boundary.km.", "Distance_coast.km.", "oxygen.umol.l.","NO3_umol.l","PO4_umol.l","Total.N..nmol.L.", "Total.C..nmol.L.", "chlorophyll")
meta_sub_PP <- c("Site","province", "SST", "salinity", "distance_to_province_boundary.km.", "Distance_coast.km.", "oxygen.umol.l.","NO3_umol.l","PO4_umol.l","Total.N..nmol.L.", "Total.C..nmol.L.", "chlorophyll", "PPAVG", "specific_PP", "biomass_transport")
meta_PCA(list_meta$meta_functions.z[meta_sub])## Loading required package: ggbiplot## Loading required package: plyr##
## Attaching package: 'plyr'## The following object is masked from 'package:ggpubr':
##
## mutate## The following object is masked from 'package:purrr':
##
## compact## Loading required package: grid## Standard deviations (1, .., p=10):
## [1] 2.3540654 1.3269331 1.1042458 0.7624836 0.6789696 0.5331532 0.2749711
## [8] 0.2207139 0.1311009 0.1006038
##
## Rotation (n x k) = (10 x 10):
## PC1 PC2 PC3
## SST 0.3673779 0.10968182 -0.32573244
## salinity 0.3122419 -0.34742938 0.08789074
## distance_to_province_boundary.km. 0.1850975 0.51353969 -0.06364393
## Distance_coast.km. 0.2174735 0.53346612 -0.34256432
## oxygen.umol.l. -0.3871913 -0.06190419 0.22076205
## NO3_umol.l -0.2998920 0.38354997 0.31667977
## PO4_umol.l -0.3337318 0.35668273 0.22483422
## Total.N..nmol.L. -0.3358382 -0.10596167 -0.46920571
## Total.C..nmol.L. -0.3403570 -0.15793851 -0.44395238
## chlorophyll -0.3257655 0.06794038 -0.38464612
## PC4 PC5 PC6
## SST 0.11082030 -0.35697893 0.05203432
## salinity 0.52472106 -0.16904645 -0.39396752
## distance_to_province_boundary.km. 0.49897645 0.64194791 -0.12897129
## Distance_coast.km. -0.28337328 -0.12966258 0.19521472
## oxygen.umol.l. -0.06526041 0.37229730 0.19506593
## NO3_umol.l 0.27564160 -0.37404505 0.02230257
## PO4_umol.l 0.15947495 -0.35835022 -0.18194640
## Total.N..nmol.L. 0.33297526 -0.05688187 0.21300573
## Total.C..nmol.L. 0.30126354 -0.02372620 0.22849614
## chlorophyll -0.27533079 0.06596586 -0.78619661
## PC7 PC8 PC9
## SST 0.48362429 -0.58958362 0.01138746
## salinity -0.49694578 -0.13740842 0.20941577
## distance_to_province_boundary.km. 0.13106153 0.03885081 -0.02475211
## Distance_coast.km. -0.60405984 -0.01789147 0.22278095
## oxygen.umol.l. -0.17562048 -0.66543193 0.26679062
## NO3_umol.l -0.20090679 -0.23059181 -0.56787043
## PO4_umol.l 0.24282674 0.21555849 0.62860391
## Total.N..nmol.L. -0.07972402 0.23690468 -0.20789802
## Total.C..nmol.L. -0.01128151 -0.08238599 0.24020080
## chlorophyll -0.02080677 -0.16227016 -0.12671383
## PC10
## SST 0.15115589
## salinity 0.07254367
## distance_to_province_boundary.km. -0.03095076
## Distance_coast.km. 0.02659906
## oxygen.umol.l. 0.26791884
## NO3_umol.l -0.17398222
## PO4_umol.l 0.15272616
## Total.N..nmol.L. 0.62502000
## Total.C..nmol.L. -0.67377633
## chlorophyll -0.01495696meta_PCA(list_meta$meta_functions.PP.z[meta_sub_PP])## Loading required package: ggbiplot## Loading required package: vegan## This is vegan 2.5-7## Standard deviations (1, .., p=10):
## [1] 2.40380606 1.27932768 1.00839653 0.81890127 0.70700174 0.51529532
## [7] 0.27959649 0.17523436 0.13373371 0.07367188
##
## Rotation (n x k) = (10 x 10):
## PC1 PC2 PC3
## SST 0.3572144 0.20436901 -0.32472022
## salinity 0.3079956 -0.31823867 -0.09365239
## distance_to_province_boundary.km. 0.1758840 0.50467819 0.04506888
## Distance_coast.km. 0.1977742 0.62451997 -0.15620873
## oxygen.umol.l. -0.3793710 -0.11881502 0.25129999
## NO3_umol.l -0.3129521 0.32125995 0.34501411
## PO4_umol.l -0.3475766 0.28145521 0.25097413
## Total.N..nmol.L. -0.3402311 0.01941654 -0.50169851
## Total.C..nmol.L. -0.3522045 -0.03222106 -0.46612731
## chlorophyll -0.3240537 0.11947798 -0.38105530
## PC4 PC5 PC6
## SST 0.014131737 -0.34971983 0.040553291
## salinity 0.524413699 -0.24729331 -0.397619921
## distance_to_province_boundary.km. 0.579871925 0.58923702 -0.080958014
## Distance_coast.km. -0.334433026 -0.07751395 0.150461254
## oxygen.umol.l. -0.007868179 0.32650850 0.158170059
## NO3_umol.l 0.239159717 -0.43602986 -0.007750222
## PO4_umol.l 0.133042038 -0.35433319 -0.256927077
## Total.N..nmol.L. 0.270168669 -0.06595402 0.264170309
## Total.C..nmol.L. 0.231004505 -0.04288111 0.271071199
## chlorophyll -0.274554211 0.18671586 -0.759411704
## PC7 PC8 PC9
## SST -0.39854029 -0.640811301 0.12565074
## salinity 0.49564302 -0.092665348 -0.20015440
## distance_to_province_boundary.km. -0.13888222 0.007283007 0.03505632
## Distance_coast.km. 0.56985201 0.036715523 -0.27574474
## oxygen.umol.l. 0.27139656 -0.687347358 -0.14668243
## NO3_umol.l 0.23839728 -0.080669406 0.57152833
## PO4_umol.l -0.34099062 0.079590929 -0.60684825
## Total.N..nmol.L. 0.04524755 0.258836649 0.18614305
## Total.C..nmol.L. 0.02932205 -0.127585506 -0.28575042
## chlorophyll 0.04257894 -0.103970221 0.18481964
## PC10
## SST 0.12561105
## salinity 0.08072252
## distance_to_province_boundary.km. -0.04192079
## Distance_coast.km. 0.06206496
## oxygen.umol.l. 0.28196326
## NO3_umol.l -0.20604222
## PO4_umol.l 0.19195743
## Total.N..nmol.L. 0.61753091
## Total.C..nmol.L. -0.65587080
## chlorophyll -0.04220259me_data <- c("SST", "salinity", "distance_to_province_boundary.km.", "Distance_coast.km.", "oxygen.umol.l.","NO3_umol.l","PO4_umol.l","Total.N..nmol.L.", "Total.C..nmol.L.", "chlorophyll")
me_data_PP <- c("SST", "salinity", "distance_to_province_boundary.km.", "Distance_coast.km.", "oxygen.umol.l.","NO3_umol.l","PO4_umol.l","Total.N..nmol.L.", "Total.C..nmol.L.", "chlorophyll", "PPAVG")
meta_PCoA(list_meta$meta_functions.z[me_data],list_meta$meta_functions.z["province"], list_meta$meta_functions.z["Site"])## Loading required package: vegan
## This is vegan 2.5-7meta_PCoA(list_meta$meta_functions.PP.z[me_data_PP],list_meta$meta_functions.PP.z["province"], list_meta$meta_functions.PP.z["Site"])## Loading required package: vegan
## This is vegan 2.5-7#meta_PCA(BRAZ[meta_sub])
rm(meta_sub, meta_sub_PP, me_data, me_data_PP)
## Loading required package: suncalc## Warning: package 'suncalc' was built under R version 4.0.5## Loading required package: vegan## This is vegan 2.5-7## Call: rda(formula = ASV.clr.t ~ oxygen.umol.l. + Total.C..nmol.L. +
## PO4_umol.l + Distance_coast.km. + SST + salinity +
## distance_to_province_boundary.km. + NO3_umol.l + chlorophyll + altitude
## + azimuth, data = meta)
##
## Inertia Proportion Rank
## Total 858.0160 1.0000
## Constrained 460.3395 0.5365 11
## Unconstrained 397.6765 0.4635 109
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10 RDA11
## 238.68 75.38 45.62 38.00 25.78 11.06 9.92 6.46 4.75 2.76 1.94
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 65.43 41.54 30.44 18.88 16.23 15.30 11.63 11.42
## (Showing 8 of 109 unconstrained eigenvalues)## R2.adj Df AIC F Pr(>F)
## + oxygen.umol.l. 0.23600 1 786.72 38.0683 0.002 **
## + Total.C..nmol.L. 0.30054 1 777.02 11.9802 0.002 **
## + PO4_umol.l 0.35334 1 768.49 10.6346 0.002 **
## + Distance_coast.km. 0.39593 1 761.21 9.2496 0.002 **
## + SST 0.42484 1 756.23 6.8307 0.002 **
## + salinity 0.44848 1 752.09 5.9295 0.002 **
## + distance_to_province_boundary.km. 0.45946 1 750.60 3.3140 0.002 **
## + NO3_umol.l 0.46994 1 749.15 3.2354 0.002 **
## + chlorophyll 0.48205 1 747.27 3.6180 0.002 **
## + altitude 0.48642 1 747.15 1.9448 0.008 **
## + azimuth 0.48974 1 747.26 1.7163 0.022 *
## <All variables> 0.49192
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Call: rda(formula = ASV.clr.t ~ oxygen.umol.l. + Total.C..nmol.L. +
## Distance_coast.km. + SST + salinity + PO4_umol.l + NO3_umol.l +
## chlorophyll + distance_to_province_boundary.km. + altitude, data =
## meta)
##
## Inertia Proportion Rank
## Total 343.2630 1.0000
## Constrained 217.2235 0.6328 10
## Unconstrained 126.0395 0.3672 58
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10
## 132.06 47.80 15.00 11.67 4.47 2.45 1.60 1.00 0.86 0.33
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 32.42 21.67 12.44 8.57 6.17 4.73 4.35 3.50
## (Showing 8 of 58 unconstrained eigenvalues)## R2.adj Df AIC F Pr(>F)
## + oxygen.umol.l. 0.29926 1 665.41 52.2482 0.002 **
## + Total.C..nmol.L. 0.38590 1 650.42 17.7896 0.002 **
## + Distance_coast.km. 0.46438 1 634.85 18.2893 0.002 **
## + SST 0.50401 1 626.51 10.3480 0.002 **
## + salinity 0.53720 1 619.08 9.3200 0.002 **
## + PO4_umol.l 0.56583 1 612.30 8.5817 0.002 **
## + NO3_umol.l 0.57518 1 610.59 3.5103 0.004 **
## + chlorophyll 0.58729 1 608.02 4.3137 0.002 **
## + distance_to_province_boundary.km. 0.59414 1 606.91 2.8912 0.002 **
## + altitude 0.59944 1 606.22 2.4687 0.016 *
## <All variables> 0.60129
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Call: rda(formula = ASV.clr.t ~ SST + salinity + oxygen.umol.l. +
## PO4_umol.l + Total.C..nmol.L. + distance_to_province_boundary.km. +
## Distance_coast.km. + chlorophyll + NO3_umol.l + azimuth, data = meta)
##
## Inertia Proportion Rank
## Total 171.2932 1.0000
## Constrained 84.7253 0.4946 10
## Unconstrained 86.5679 0.5054 55
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10
## 41.51 18.97 8.56 4.76 4.20 3.15 1.53 1.23 0.51 0.30
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 12.478 11.766 7.279 4.944 4.096 3.615 3.309 3.034
## (Showing 8 of 55 unconstrained eigenvalues)## R2.adj Df AIC F Pr(>F)
## + SST 0.17782 1 600.64 26.9543 0.002 **
## + salinity 0.26778 1 587.60 15.6198 0.002 **
## + oxygen.umol.l. 0.31485 1 580.53 9.1056 0.002 **
## + PO4_umol.l 0.35921 1 573.39 9.1008 0.002 **
## + Total.C..nmol.L. 0.38859 1 568.67 6.5726 0.002 **
## + distance_to_province_boundary.km. 0.40915 1 565.47 5.0034 0.002 **
## + Distance_coast.km. 0.42946 1 562.17 5.0575 0.002 **
## + chlorophyll 0.44052 1 560.73 3.2335 0.002 **
## + NO3_umol.l 0.44489 1 560.69 1.8826 0.016 *
## + azimuth 0.44868 1 560.77 1.7619 0.044 *
## <All variables> 0.45168
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Call: rda(formula = ASV.clr.t ~ SST + salinity + Total.C..nmol.L. +
## PO4_umol.l + oxygen.umol.l. + Distance_coast.km. +
## distance_to_province_boundary.km. + chlorophyll + NO3_umol.l + altitude
## + azimuth, data = meta)
##
## Inertia Proportion Rank
## Total 2391.2179 1.0000
## Constrained 1043.5874 0.4364 11
## Unconstrained 1347.6304 0.5636 109
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10 RDA11
## 426.9 181.7 130.8 89.4 82.3 44.0 33.2 19.8 17.8 9.8 7.9
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 196.99 105.35 70.78 56.10 54.67 47.74 37.70 35.80
## (Showing 8 of 109 unconstrained eigenvalues)## R2.adj Df AIC F Pr(>F)
## + SST 0.14810 1 923.91 21.8619 0.002 **
## + salinity 0.20422 1 916.65 9.3911 0.002 **
## + Total.C..nmol.L. 0.25110 1 910.27 8.3880 0.002 **
## + PO4_umol.l 0.28554 1 905.54 6.6388 0.002 **
## + oxygen.umol.l. 0.31599 1 901.22 6.1647 0.002 **
## + Distance_coast.km. 0.33967 1 897.90 5.1229 0.002 **
## + distance_to_province_boundary.km. 0.35578 1 895.84 3.8519 0.002 **
## + chlorophyll 0.36468 1 895.09 2.5820 0.002 **
## + NO3_umol.l 0.37109 1 894.77 2.1419 0.004 **
## + altitude 0.37684 1 894.57 2.0252 0.008 **
## + azimuth 0.37955 1 894.93 1.4800 0.024 *
## <All variables> 0.37993
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Call: rda(formula = ASV.clr.t ~ SST + Distance_coast.km. +
## Total.C..nmol.L. + oxygen.umol.l. + PO4_umol.l + salinity +
## distance_to_province_boundary.km. + chlorophyll + NO3_umol.l +
## altitude, data = meta)
##
## Inertia Proportion Rank
## Total 4734.8559 1.0000
## Constrained 2720.5440 0.5746 10
## Unconstrained 2014.3119 0.4254 110
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10
## 1517.3 398.1 329.8 174.4 139.6 63.6 36.9 28.8 21.6 10.6
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 486.9 180.0 157.7 81.8 72.6 62.6 56.6 50.8
## (Showing 8 of 110 unconstrained eigenvalues)## R2.adj Df AIC F Pr(>F)
## + SST 0.25994 1 989.55 43.1480 0.002 **
## + Distance_coast.km. 0.33743 1 977.14 14.9191 0.002 **
## + Total.C..nmol.L. 0.40558 1 964.98 14.5273 0.002 **
## + oxygen.umol.l. 0.44350 1 957.96 8.9741 0.002 **
## + PO4_umol.l 0.48072 1 950.54 9.3131 0.002 **
## + salinity 0.49790 1 947.41 4.9362 0.002 **
## + distance_to_province_boundary.km. 0.50781 1 945.93 3.2948 0.002 **
## + chlorophyll 0.51701 1 944.58 3.1527 0.006 **
## + NO3_umol.l 0.52740 1 942.86 3.4624 0.004 **
## + altitude 0.53590 1 941.57 3.0328 0.008 **
## <All variables> 0.53989
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Loading required package: raster## Loading required package: sp##
## Attaching package: 'sp'## The following object is masked from 'package:coda.base':
##
## coordinates##
## Attaching package: 'raster'## The following object is masked from 'package:ggpubr':
##
## rotate## The following object is masked from 'package:NADA':
##
## flip## The following objects are masked from 'package:MASS':
##
## area, select## The following object is masked from 'package:tidyr':
##
## extract## Call: rda(formula = ASV.clr.t.sort ~ SST + salinity +
## distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l.
## + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. +
## chlorophyll + altitude + azimuth, data = meta.wf.data)
##
## Inertia Proportion Rank
## Total 858.0160 1.0000
## Constrained 465.6719 0.5427 12
## Unconstrained 392.3441 0.4573 108
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10 RDA11
## 238.68 75.77 45.72 38.08 25.96 12.16 9.93 6.47 4.79 4.10 2.19
## RDA12
## 1.82
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 64.78 41.25 30.28 18.78 16.15 14.94 11.47 11.37
## (Showing 8 of 108 unconstrained eigenvalues)
##
## [1] "mean distances of sites from centroids"
## # A tibble: 11 x 2
## province mean
## * <fct> <dbl>
## 1 BRAZ 0.0497
## 2 CNRY 0.0934
## 3 FKLD 0.0378
## 4 NADR 0.0279
## 5 NAST-E 0.0485
## 6 NATR 0.0373
## 7 SATL-COLD 0.0251
## 8 SATL-HOT 0.0346
## 9 Station24 0
## 10 Station92 0
## 11 WTRA 0.0387
## [1] "distances between high/low PP province"
## $BRAZ_BRAZ
## [1] 0
##
## $BRAZ_CNRY
## [1] 0.0916648
##
## $BRAZ_FKLD
## [1] 0.08673431
##
## $BRAZ_NADR
## [1] 0.1852124
##
## $`BRAZ_NAST-E`
## [1] 0.2119694
##
## $BRAZ_NATR
## [1] 0.1634472
##
## $`BRAZ_SATL-COLD`
## [1] 0.220872
##
## $`BRAZ_SATL-HOT`
## [1] 0.2456477
##
## $BRAZ_Station24
## [1] 0.1779868
##
## $BRAZ_Station92
## [1] 0.239781
##
## $BRAZ_WTRA
## [1] 0.2410666
##
## $CNRY_BRAZ
## [1] 0.0916648
##
## $CNRY_CNRY
## [1] 0
##
## $CNRY_FKLD
## [1] 0.1241782
##
## $CNRY_NADR
## [1] 0.1925774
##
## $`CNRY_NAST-E`
## [1] 0.1673032
##
## $CNRY_NATR
## [1] 0.08844391
##
## $`CNRY_SATL-COLD`
## [1] 0.1421868
##
## $`CNRY_SATL-HOT`
## [1] 0.1574646
##
## $CNRY_Station24
## [1] 0.09740441
##
## $CNRY_Station92
## [1] 0.1485428
##
## $CNRY_WTRA
## [1] 0.1494686
##
## $FKLD_BRAZ
## [1] 0.08673431
##
## $FKLD_CNRY
## [1] 0.1241782
##
## $FKLD_FKLD
## [1] 0
##
## $FKLD_NADR
## [1] 0.09994069
##
## $`FKLD_NAST-E`
## [1] 0.1543748
##
## $FKLD_NATR
## [1] 0.2123918
##
## $`FKLD_SATL-COLD`
## [1] 0.1989319
##
## $`FKLD_SATL-HOT`
## [1] 0.2392797
##
## $FKLD_Station24
## [1] 0.1659888
##
## $FKLD_Station92
## [1] 0.2585588
##
## $FKLD_WTRA
## [1] 0.2560555
##
## $NADR_BRAZ
## [1] 0.1852124
##
## $NADR_CNRY
## [1] 0.1925774
##
## $NADR_FKLD
## [1] 0.09994069
##
## $NADR_NADR
## [1] 0
##
## $`NADR_NAST-E`
## [1] 0.1098027
##
## $NADR_NATR
## [1] 0.2766355
##
## $`NADR_SATL-COLD`
## [1] 0.1944429
##
## $`NADR_SATL-HOT`
## [1] 0.2457118
##
## $NADR_Station24
## [1] 0.1820507
##
## $NADR_Station92
## [1] 0.2894505
##
## $NADR_WTRA
## [1] 0.2833553
##
## $`NAST-E_BRAZ`
## [1] 0.2119694
##
## $`NAST-E_CNRY`
## [1] 0.1673032
##
## $`NAST-E_FKLD`
## [1] 0.1543748
##
## $`NAST-E_NADR`
## [1] 0.1098027
##
## $`NAST-E_NAST-E`
## [1] 0
##
## $`NAST-E_NATR`
## [1] 0.2283782
##
## $`NAST-E_SATL-COLD`
## [1] 0.09489192
##
## $`NAST-E_SATL-HOT`
## [1] 0.1475586
##
## $`NAST-E_Station24`
## [1] 0.1028692
##
## $`NAST-E_Station92`
## [1] 0.205344
##
## $`NAST-E_WTRA`
## [1] 0.1968591
##
## $NATR_BRAZ
## [1] 0.1634472
##
## $NATR_CNRY
## [1] 0.08844391
##
## $NATR_FKLD
## [1] 0.2123918
##
## $NATR_NADR
## [1] 0.2766355
##
## $`NATR_NAST-E`
## [1] 0.2283782
##
## $NATR_NATR
## [1] 0
##
## $`NATR_SATL-COLD`
## [1] 0.1661472
##
## $`NATR_SATL-HOT`
## [1] 0.1513253
##
## $NATR_Station24
## [1] 0.1305746
##
## $NATR_Station92
## [1] 0.1027786
##
## $NATR_WTRA
## [1] 0.1100034
##
## $`SATL-COLD_BRAZ`
## [1] 0.220872
##
## $`SATL-COLD_CNRY`
## [1] 0.1421868
##
## $`SATL-COLD_FKLD`
## [1] 0.1989319
##
## $`SATL-COLD_NADR`
## [1] 0.1944429
##
## $`SATL-COLD_NAST-E`
## [1] 0.09489192
##
## $`SATL-COLD_NATR`
## [1] 0.1661472
##
## $`SATL-COLD_SATL-COLD`
## [1] 0
##
## $`SATL-COLD_SATL-HOT`
## [1] 0.05276013
##
## $`SATL-COLD_Station24`
## [1] 0.04478316
##
## $`SATL-COLD_Station92`
## [1] 0.1145724
##
## $`SATL-COLD_WTRA`
## [1] 0.1049822
##
## $`SATL-HOT_BRAZ`
## [1] 0.2456477
##
## $`SATL-HOT_CNRY`
## [1] 0.1574646
##
## $`SATL-HOT_FKLD`
## [1] 0.2392797
##
## $`SATL-HOT_NADR`
## [1] 0.2457118
##
## $`SATL-HOT_NAST-E`
## [1] 0.1475586
##
## $`SATL-HOT_NATR`
## [1] 0.1513253
##
## $`SATL-HOT_SATL-COLD`
## [1] 0.05276013
##
## $`SATL-HOT_SATL-HOT`
## [1] 0
##
## $`SATL-HOT_Station24`
## [1] 0.07332464
##
## $`SATL-HOT_Station92`
## [1] 0.07176503
##
## $`SATL-HOT_WTRA`
## [1] 0.06083844
##
## $Station24_BRAZ
## [1] 0.1779868
##
## $Station24_CNRY
## [1] 0.09740441
##
## $Station24_FKLD
## [1] 0.1659888
##
## $Station24_NADR
## [1] 0.1820507
##
## $`Station24_NAST-E`
## [1] 0.1028692
##
## $Station24_NATR
## [1] 0.1305746
##
## $`Station24_SATL-COLD`
## [1] 0.04478316
##
## $`Station24_SATL-HOT`
## [1] 0.07332464
##
## $Station24_Station24
## [1] 0
##
## $Station24_Station92
## [1] 0.1078217
##
## $Station24_WTRA
## [1] 0.1013258
##
## $Station92_BRAZ
## [1] 0.239781
##
## $Station92_CNRY
## [1] 0.1485428
##
## $Station92_FKLD
## [1] 0.2585588
##
## $Station92_NADR
## [1] 0.2894505
##
## $`Station92_NAST-E`
## [1] 0.205344
##
## $Station92_NATR
## [1] 0.1027786
##
## $`Station92_SATL-COLD`
## [1] 0.1145724
##
## $`Station92_SATL-HOT`
## [1] 0.07176503
##
## $Station92_Station24
## [1] 0.1078217
##
## $Station92_Station92
## [1] 0
##
## $Station92_WTRA
## [1] 0.01109426
##
## $WTRA_BRAZ
## [1] 0.2410666
##
## $WTRA_CNRY
## [1] 0.1494686
##
## $WTRA_FKLD
## [1] 0.2560555
##
## $WTRA_NADR
## [1] 0.2833553
##
## $`WTRA_NAST-E`
## [1] 0.1968591
##
## $WTRA_NATR
## [1] 0.1100034
##
## $`WTRA_SATL-COLD`
## [1] 0.1049822
##
## $`WTRA_SATL-HOT`
## [1] 0.06083844
##
## $WTRA_Station24
## [1] 0.1013258
##
## $WTRA_Station92
## [1] 0.01109426
##
## $WTRA_WTRA
## [1] 0## Permutation test for rda under reduced model
## Permutation: free
## Number of permutations: 999
##
## Model: rda(formula = ASV.clr.t.sort ~ SST + salinity + distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l. + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. + chlorophyll + altitude + azimuth, data = meta.wf.data)
## Df Variance F Pr(>F)
## Model 12 465.67 10.682 0.001 ***
## Residual 108 392.34
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.542731## Call: rda(formula = ASV.clr.t.sort ~ SST + salinity +
## distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l.
## + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. +
## chlorophyll + altitude + azimuth, data = meta.wf.data)
##
## Inertia Proportion Rank
## Total 343.2630 1.0000
## Constrained 220.0884 0.6412 12
## Unconstrained 123.1746 0.3588 58
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10 RDA11
## 133.06 47.88 15.46 11.72 4.85 2.52 1.66 1.09 0.91 0.48 0.26
## RDA12
## 0.20
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 32.40 21.45 10.93 8.41 6.16 4.66 4.32 3.46
## (Showing 8 of 58 unconstrained eigenvalues)
##
## [1] "mean distances of sites from centroids"
## # A tibble: 11 x 2
## province mean
## * <fct> <dbl>
## 1 BRAZ 0.0571
## 2 CNRY 0.0841
## 3 FKLD 0.0284
## 4 NADR 0.0283
## 5 NAST-E 0.0249
## 6 NATR 0.0256
## 7 SATL-COLD 0.0258
## 8 SATL-HOT 0.0311
## 9 Station24 0
## 10 Station92 0
## 11 WTRA 0.0598
## [1] "distances between high/low PP province"
## $BRAZ_BRAZ
## [1] 0
##
## $BRAZ_CNRY
## [1] 0.06584233
##
## $BRAZ_FKLD
## [1] 0.03474786
##
## $BRAZ_NADR
## [1] 0.07059743
##
## $`BRAZ_NAST-E`
## [1] 0.1856224
##
## $BRAZ_NATR
## [1] 0.1618059
##
## $`BRAZ_SATL-COLD`
## [1] 0.2218084
##
## $`BRAZ_SATL-HOT`
## [1] 0.2113061
##
## $BRAZ_Station24
## [1] 0.2222517
##
## $BRAZ_Station92
## [1] 0.2321051
##
## $BRAZ_WTRA
## [1] 0.2434729
##
## $CNRY_BRAZ
## [1] 0.06584233
##
## $CNRY_CNRY
## [1] 0
##
## $CNRY_FKLD
## [1] 0.04687971
##
## $CNRY_NADR
## [1] 0.1136606
##
## $`CNRY_NAST-E`
## [1] 0.1698931
##
## $CNRY_NATR
## [1] 0.1017896
##
## $`CNRY_SATL-COLD`
## [1] 0.1743244
##
## $`CNRY_SATL-HOT`
## [1] 0.1516779
##
## $CNRY_Station24
## [1] 0.1872376
##
## $CNRY_Station92
## [1] 0.1673489
##
## $CNRY_WTRA
## [1] 0.1798933
##
## $FKLD_BRAZ
## [1] 0.03474786
##
## $FKLD_CNRY
## [1] 0.04687971
##
## $FKLD_FKLD
## [1] 0
##
## $FKLD_NADR
## [1] 0.06703234
##
## $`FKLD_NAST-E`
## [1] 0.1542382
##
## $FKLD_NATR
## [1] 0.1486672
##
## $`FKLD_SATL-COLD`
## [1] 0.187246
##
## $`FKLD_SATL-HOT`
## [1] 0.1795713
##
## $FKLD_Station24
## [1] 0.1878398
##
## $FKLD_Station92
## [1] 0.212411
##
## $FKLD_WTRA
## [1] 0.2258471
##
## $NADR_BRAZ
## [1] 0.07059743
##
## $NADR_CNRY
## [1] 0.1136606
##
## $NADR_FKLD
## [1] 0.06703234
##
## $NADR_NADR
## [1] 0
##
## $`NADR_NAST-E`
## [1] 0.1465567
##
## $NADR_NATR
## [1] 0.215326
##
## $`NADR_SATL-COLD`
## [1] 0.2148902
##
## $`NADR_SATL-HOT`
## [1] 0.2248686
##
## $NADR_Station24
## [1] 0.1996321
##
## $NADR_Station92
## [1] 0.275743
##
## $NADR_WTRA
## [1] 0.2903665
##
## $`NAST-E_BRAZ`
## [1] 0.1856224
##
## $`NAST-E_CNRY`
## [1] 0.1698931
##
## $`NAST-E_FKLD`
## [1] 0.1542382
##
## $`NAST-E_NADR`
## [1] 0.1465567
##
## $`NAST-E_NAST-E`
## [1] 0
##
## $`NAST-E_NATR`
## [1] 0.2352995
##
## $`NAST-E_SATL-COLD`
## [1] 0.1060818
##
## $`NAST-E_SATL-HOT`
## [1] 0.1538914
##
## $`NAST-E_Station24`
## [1] 0.06643292
##
## $`NAST-E_Station92`
## [1] 0.2565875
##
## $`NAST-E_WTRA`
## [1] 0.2763867
##
## $NATR_BRAZ
## [1] 0.1618059
##
## $NATR_CNRY
## [1] 0.1017896
##
## $NATR_FKLD
## [1] 0.1486672
##
## $NATR_NADR
## [1] 0.215326
##
## $`NATR_NAST-E`
## [1] 0.2352995
##
## $NATR_NATR
## [1] 0
##
## $`NATR_SATL-COLD`
## [1] 0.1891556
##
## $`NATR_SATL-HOT`
## [1] 0.1355933
##
## $NATR_Station24
## [1] 0.2239064
##
## $NATR_Station92
## [1] 0.07813549
##
## $NATR_WTRA
## [1] 0.08429333
##
## $`SATL-COLD_BRAZ`
## [1] 0.2218084
##
## $`SATL-COLD_CNRY`
## [1] 0.1743244
##
## $`SATL-COLD_FKLD`
## [1] 0.187246
##
## $`SATL-COLD_NADR`
## [1] 0.2148902
##
## $`SATL-COLD_NAST-E`
## [1] 0.1060818
##
## $`SATL-COLD_NATR`
## [1] 0.1891556
##
## $`SATL-COLD_SATL-COLD`
## [1] 0
##
## $`SATL-COLD_SATL-HOT`
## [1] 0.06337667
##
## $`SATL-COLD_Station24`
## [1] 0.04937072
##
## $`SATL-COLD_Station92`
## [1] 0.1791403
##
## $`SATL-COLD_WTRA`
## [1] 0.1993936
##
## $`SATL-HOT_BRAZ`
## [1] 0.2113061
##
## $`SATL-HOT_CNRY`
## [1] 0.1516779
##
## $`SATL-HOT_FKLD`
## [1] 0.1795713
##
## $`SATL-HOT_NADR`
## [1] 0.2248686
##
## $`SATL-HOT_NAST-E`
## [1] 0.1538914
##
## $`SATL-HOT_NATR`
## [1] 0.1355933
##
## $`SATL-HOT_SATL-COLD`
## [1] 0.06337667
##
## $`SATL-HOT_SATL-HOT`
## [1] 0
##
## $`SATL-HOT_Station24`
## [1] 0.1104001
##
## $`SATL-HOT_Station92`
## [1] 0.1158528
##
## $`SATL-HOT_WTRA`
## [1] 0.1360662
##
## $Station24_BRAZ
## [1] 0.2222517
##
## $Station24_CNRY
## [1] 0.1872376
##
## $Station24_FKLD
## [1] 0.1878398
##
## $Station24_NADR
## [1] 0.1996321
##
## $`Station24_NAST-E`
## [1] 0.06643292
##
## $Station24_NATR
## [1] 0.2239064
##
## $`Station24_SATL-COLD`
## [1] 0.04937072
##
## $`Station24_SATL-HOT`
## [1] 0.1104001
##
## $Station24_Station24
## [1] 0
##
## $Station24_Station92
## [1] 0.2245435
##
## $Station24_WTRA
## [1] 0.2448864
##
## $Station92_BRAZ
## [1] 0.2321051
##
## $Station92_CNRY
## [1] 0.1673489
##
## $Station92_FKLD
## [1] 0.212411
##
## $Station92_NADR
## [1] 0.275743
##
## $`Station92_NAST-E`
## [1] 0.2565875
##
## $Station92_NATR
## [1] 0.07813549
##
## $`Station92_SATL-COLD`
## [1] 0.1791403
##
## $`Station92_SATL-HOT`
## [1] 0.1158528
##
## $Station92_Station24
## [1] 0.2245435
##
## $Station92_Station92
## [1] 0
##
## $Station92_WTRA
## [1] 0.02034297
##
## $WTRA_BRAZ
## [1] 0.2434729
##
## $WTRA_CNRY
## [1] 0.1798933
##
## $WTRA_FKLD
## [1] 0.2258471
##
## $WTRA_NADR
## [1] 0.2903665
##
## $`WTRA_NAST-E`
## [1] 0.2763867
##
## $WTRA_NATR
## [1] 0.08429333
##
## $`WTRA_SATL-COLD`
## [1] 0.1993936
##
## $`WTRA_SATL-HOT`
## [1] 0.1360662
##
## $WTRA_Station24
## [1] 0.2448864
##
## $WTRA_Station92
## [1] 0.02034297
##
## $WTRA_WTRA
## [1] 0## Permutation test for rda under reduced model
## Permutation: free
## Number of permutations: 999
##
## Model: rda(formula = ASV.clr.t.sort ~ SST + salinity + distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l. + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. + chlorophyll + altitude + azimuth, data = meta.wf.data)
## Df Variance F Pr(>F)
## Model 12 220.09 16.081 0.001 ***
## Residual 108 123.17
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.6411655## Call: rda(formula = ASV.clr.t.sort ~ SST + salinity +
## distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l.
## + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. +
## chlorophyll + altitude + azimuth, data = meta.wf.data)
##
## Inertia Proportion Rank
## Total 171.2932 1.0000
## Constrained 86.7617 0.5065 12
## Unconstrained 84.5316 0.4935 55
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10 RDA11 RDA12
## 41.52 19.34 8.59 4.88 4.45 3.18 1.58 1.26 0.67 0.66 0.34 0.28
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 12.224 11.250 7.087 4.911 4.043 3.595 3.296 2.975
## (Showing 8 of 55 unconstrained eigenvalues)
##
## [1] "mean distances of sites from centroids"
## # A tibble: 11 x 2
## province mean
## * <fct> <dbl>
## 1 BRAZ 0.0656
## 2 CNRY 0.0584
## 3 FKLD 0.0166
## 4 NADR 0.0346
## 5 NAST-E 0.0369
## 6 NATR 0.0322
## 7 SATL-COLD 0.0299
## 8 SATL-HOT 0.0324
## 9 Station24 0
## 10 Station92 0
## 11 WTRA 0.0588
## [1] "distances between high/low PP province"
## $BRAZ_BRAZ
## [1] 0
##
## $BRAZ_CNRY
## [1] 0.09005413
##
## $BRAZ_FKLD
## [1] 0.04557466
##
## $BRAZ_NADR
## [1] 0.1122421
##
## $`BRAZ_NAST-E`
## [1] 0.1744032
##
## $BRAZ_NATR
## [1] 0.1289371
##
## $`BRAZ_SATL-COLD`
## [1] 0.1977782
##
## $`BRAZ_SATL-HOT`
## [1] 0.2097399
##
## $BRAZ_Station24
## [1] 0.2289646
##
## $BRAZ_Station92
## [1] 0.1850615
##
## $BRAZ_WTRA
## [1] 0.1916724
##
## $CNRY_BRAZ
## [1] 0.09005413
##
## $CNRY_CNRY
## [1] 0
##
## $CNRY_FKLD
## [1] 0.04542087
##
## $CNRY_NADR
## [1] 0.156284
##
## $`CNRY_NAST-E`
## [1] 0.1008408
##
## $CNRY_NATR
## [1] 0.09561091
##
## $`CNRY_SATL-COLD`
## [1] 0.1078467
##
## $`CNRY_SATL-HOT`
## [1] 0.1299028
##
## $CNRY_Station24
## [1] 0.1398011
##
## $CNRY_Station92
## [1] 0.1539934
##
## $CNRY_WTRA
## [1] 0.1934524
##
## $FKLD_BRAZ
## [1] 0.04557466
##
## $FKLD_CNRY
## [1] 0.04542087
##
## $FKLD_FKLD
## [1] 0
##
## $FKLD_NADR
## [1] 0.1228678
##
## $`FKLD_NAST-E`
## [1] 0.1315715
##
## $FKLD_NATR
## [1] 0.1101782
##
## $`FKLD_SATL-COLD`
## [1] 0.1531813
##
## $`FKLD_SATL-HOT`
## [1] 0.1715038
##
## $FKLD_Station24
## [1] 0.1834227
##
## $FKLD_Station92
## [1] 0.1702635
##
## $FKLD_WTRA
## [1] 0.193754
##
## $NADR_BRAZ
## [1] 0.1122421
##
## $NADR_CNRY
## [1] 0.156284
##
## $NADR_FKLD
## [1] 0.1228678
##
## $NADR_NADR
## [1] 0
##
## $`NADR_NAST-E`
## [1] 0.1815495
##
## $NADR_NATR
## [1] 0.2321196
##
## $`NADR_SATL-COLD`
## [1] 0.2480975
##
## $`NADR_SATL-HOT`
## [1] 0.2852662
##
## $NADR_Station24
## [1] 0.2624511
##
## $NADR_Station92
## [1] 0.2914926
##
## $NADR_WTRA
## [1] 0.3038786
##
## $`NAST-E_BRAZ`
## [1] 0.1744032
##
## $`NAST-E_CNRY`
## [1] 0.1008408
##
## $`NAST-E_FKLD`
## [1] 0.1315715
##
## $`NAST-E_NADR`
## [1] 0.1815495
##
## $`NAST-E_NAST-E`
## [1] 0
##
## $`NAST-E_NATR`
## [1] 0.1846998
##
## $`NAST-E_SATL-COLD`
## [1] 0.09188748
##
## $`NAST-E_SATL-HOT`
## [1] 0.1555172
##
## $`NAST-E_Station24`
## [1] 0.08609624
##
## $`NAST-E_Station92`
## [1] 0.2346996
##
## $`NAST-E_WTRA`
## [1] 0.2868069
##
## $NATR_BRAZ
## [1] 0.1289371
##
## $NATR_CNRY
## [1] 0.09561091
##
## $NATR_FKLD
## [1] 0.1101782
##
## $NATR_NADR
## [1] 0.2321196
##
## $`NATR_NAST-E`
## [1] 0.1846998
##
## $NATR_NATR
## [1] 0
##
## $`NATR_SATL-COLD`
## [1] 0.1416493
##
## $`NATR_SATL-HOT`
## [1] 0.1107877
##
## $NATR_Station24
## [1] 0.1855698
##
## $NATR_Station92
## [1] 0.06028452
##
## $NATR_WTRA
## [1] 0.1022495
##
## $`SATL-COLD_BRAZ`
## [1] 0.1977782
##
## $`SATL-COLD_CNRY`
## [1] 0.1078467
##
## $`SATL-COLD_FKLD`
## [1] 0.1531813
##
## $`SATL-COLD_NADR`
## [1] 0.2480975
##
## $`SATL-COLD_NAST-E`
## [1] 0.09188748
##
## $`SATL-COLD_NATR`
## [1] 0.1416493
##
## $`SATL-COLD_SATL-COLD`
## [1] 0
##
## $`SATL-COLD_SATL-HOT`
## [1] 0.06816535
##
## $`SATL-COLD_Station24`
## [1] 0.0443501
##
## $`SATL-COLD_Station92`
## [1] 0.1735261
##
## $`SATL-COLD_WTRA`
## [1] 0.2381359
##
## $`SATL-HOT_BRAZ`
## [1] 0.2097399
##
## $`SATL-HOT_CNRY`
## [1] 0.1299028
##
## $`SATL-HOT_FKLD`
## [1] 0.1715038
##
## $`SATL-HOT_NADR`
## [1] 0.2852662
##
## $`SATL-HOT_NAST-E`
## [1] 0.1555172
##
## $`SATL-HOT_NATR`
## [1] 0.1107877
##
## $`SATL-HOT_SATL-COLD`
## [1] 0.06816535
##
## $`SATL-HOT_SATL-HOT`
## [1] 0
##
## $`SATL-HOT_Station24`
## [1] 0.1057968
##
## $`SATL-HOT_Station92`
## [1] 0.1204412
##
## $`SATL-HOT_WTRA`
## [1] 0.1903798
##
## $Station24_BRAZ
## [1] 0.2289646
##
## $Station24_CNRY
## [1] 0.1398011
##
## $Station24_FKLD
## [1] 0.1834227
##
## $Station24_NADR
## [1] 0.2624511
##
## $`Station24_NAST-E`
## [1] 0.08609624
##
## $Station24_NATR
## [1] 0.1855698
##
## $`Station24_SATL-COLD`
## [1] 0.0443501
##
## $`Station24_SATL-HOT`
## [1] 0.1057968
##
## $Station24_Station24
## [1] 0
##
## $Station24_Station92
## [1] 0.2173768
##
## $Station24_WTRA
## [1] 0.2824744
##
## $Station92_BRAZ
## [1] 0.1850615
##
## $Station92_CNRY
## [1] 0.1539934
##
## $Station92_FKLD
## [1] 0.1702635
##
## $Station92_NADR
## [1] 0.2914926
##
## $`Station92_NAST-E`
## [1] 0.2346996
##
## $Station92_NATR
## [1] 0.06028452
##
## $`Station92_SATL-COLD`
## [1] 0.1735261
##
## $`Station92_SATL-HOT`
## [1] 0.1204412
##
## $Station92_Station24
## [1] 0.2173768
##
## $Station92_Station92
## [1] 0
##
## $Station92_WTRA
## [1] 0.07086334
##
## $WTRA_BRAZ
## [1] 0.1916724
##
## $WTRA_CNRY
## [1] 0.1934524
##
## $WTRA_FKLD
## [1] 0.193754
##
## $WTRA_NADR
## [1] 0.3038786
##
## $`WTRA_NAST-E`
## [1] 0.2868069
##
## $WTRA_NATR
## [1] 0.1022495
##
## $`WTRA_SATL-COLD`
## [1] 0.2381359
##
## $`WTRA_SATL-HOT`
## [1] 0.1903798
##
## $WTRA_Station24
## [1] 0.2824744
##
## $WTRA_Station92
## [1] 0.07086334
##
## $WTRA_WTRA
## [1] 0## Permutation test for rda under reduced model
## Permutation: free
## Number of permutations: 999
##
## Model: rda(formula = ASV.clr.t.sort ~ SST + salinity + distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l. + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. + chlorophyll + altitude + azimuth, data = meta.wf.data)
## Df Variance F Pr(>F)
## Model 12 86.762 9.2374 0.001 ***
## Residual 108 84.532
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.5065096## Call: rda(formula = ASV.clr.t.sort ~ SST + salinity +
## distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l.
## + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. +
## chlorophyll + altitude + azimuth, data = meta.wf.data)
##
## Inertia Proportion Rank
## Total 2391.2179 1.0000
## Constrained 1056.7666 0.4419 12
## Unconstrained 1334.4513 0.5581 108
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10 RDA11 RDA12
## 427.0 181.8 131.5 89.4 82.4 44.3 33.4 21.3 18.0 11.2 8.7 7.7
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 196.90 105.31 70.24 55.80 54.61 47.74 37.70 35.14
## (Showing 8 of 108 unconstrained eigenvalues)
##
## [1] "mean distances of sites from centroids"
## # A tibble: 11 x 2
## province mean
## * <fct> <dbl>
## 1 BRAZ 0.0585
## 2 CNRY 0.0704
## 3 FKLD 0.0287
## 4 NADR 0.0242
## 5 NAST-E 0.0137
## 6 NATR 0.0446
## 7 SATL-COLD 0.0374
## 8 SATL-HOT 0.0329
## 9 Station24 0
## 10 Station92 0
## 11 WTRA 0.0583
## [1] "distances between high/low PP province"
## $BRAZ_BRAZ
## [1] 0
##
## $BRAZ_CNRY
## [1] 0.09474605
##
## $BRAZ_FKLD
## [1] 0.06360947
##
## $BRAZ_NADR
## [1] 0.08572089
##
## $`BRAZ_NAST-E`
## [1] 0.196927
##
## $BRAZ_NATR
## [1] 0.1518823
##
## $`BRAZ_SATL-COLD`
## [1] 0.2088122
##
## $`BRAZ_SATL-HOT`
## [1] 0.2605315
##
## $BRAZ_Station24
## [1] 0.1870998
##
## $BRAZ_Station92
## [1] 0.2339766
##
## $BRAZ_WTRA
## [1] 0.2459185
##
## $CNRY_BRAZ
## [1] 0.09474605
##
## $CNRY_CNRY
## [1] 0
##
## $CNRY_FKLD
## [1] 0.06239775
##
## $CNRY_NADR
## [1] 0.09984299
##
## $`CNRY_NAST-E`
## [1] 0.1234617
##
## $CNRY_NATR
## [1] 0.1135349
##
## $`CNRY_SATL-COLD`
## [1] 0.1163207
##
## $`CNRY_SATL-HOT`
## [1] 0.1658735
##
## $CNRY_Station24
## [1] 0.1015087
##
## $CNRY_Station92
## [1] 0.1709937
##
## $CNRY_WTRA
## [1] 0.1936017
##
## $FKLD_BRAZ
## [1] 0.06360947
##
## $FKLD_CNRY
## [1] 0.06239775
##
## $FKLD_FKLD
## [1] 0
##
## $FKLD_NADR
## [1] 0.04011733
##
## $`FKLD_NAST-E`
## [1] 0.1351507
##
## $FKLD_NATR
## [1] 0.1636771
##
## $`FKLD_SATL-COLD`
## [1] 0.1580855
##
## $`FKLD_SATL-HOT`
## [1] 0.2181232
##
## $FKLD_Station24
## [1] 0.1306556
##
## $FKLD_Station92
## [1] 0.2312422
##
## $FKLD_WTRA
## [1] 0.251249
##
## $NADR_BRAZ
## [1] 0.08572089
##
## $NADR_CNRY
## [1] 0.09984299
##
## $NADR_FKLD
## [1] 0.04011733
##
## $NADR_NADR
## [1] 0
##
## $`NADR_NAST-E`
## [1] 0.1391792
##
## $NADR_NATR
## [1] 0.2037628
##
## $`NADR_SATL-COLD`
## [1] 0.1783408
##
## $`NADR_SATL-HOT`
## [1] 0.2432495
##
## $NADR_Station24
## [1] 0.1456302
##
## $NADR_Station92
## [1] 0.2703484
##
## $NADR_WTRA
## [1] 0.2910877
##
## $`NAST-E_BRAZ`
## [1] 0.196927
##
## $`NAST-E_CNRY`
## [1] 0.1234617
##
## $`NAST-E_FKLD`
## [1] 0.1351507
##
## $`NAST-E_NADR`
## [1] 0.1391792
##
## $`NAST-E_NAST-E`
## [1] 0
##
## $`NAST-E_NATR`
## [1] 0.2215116
##
## $`NAST-E_SATL-COLD`
## [1] 0.07174402
##
## $`NAST-E_SATL-HOT`
## [1] 0.1379642
##
## $`NAST-E_Station24`
## [1] 0.03867135
##
## $`NAST-E_Station92`
## [1] 0.2439272
##
## $`NAST-E_WTRA`
## [1] 0.275562
##
## $NATR_BRAZ
## [1] 0.1518823
##
## $NATR_CNRY
## [1] 0.1135349
##
## $NATR_FKLD
## [1] 0.1636771
##
## $NATR_NADR
## [1] 0.2037628
##
## $`NATR_NAST-E`
## [1] 0.2215116
##
## $NATR_NATR
## [1] 0
##
## $`NATR_SATL-COLD`
## [1] 0.1807059
##
## $`NATR_SATL-HOT`
## [1] 0.1904544
##
## $NATR_Station24
## [1] 0.188135
##
## $NATR_Station92
## [1] 0.08763472
##
## $NATR_WTRA
## [1] 0.09419016
##
## $`SATL-COLD_BRAZ`
## [1] 0.2088122
##
## $`SATL-COLD_CNRY`
## [1] 0.1163207
##
## $`SATL-COLD_FKLD`
## [1] 0.1580855
##
## $`SATL-COLD_NADR`
## [1] 0.1783408
##
## $`SATL-COLD_NAST-E`
## [1] 0.07174402
##
## $`SATL-COLD_NATR`
## [1] 0.1807059
##
## $`SATL-COLD_SATL-COLD`
## [1] 0
##
## $`SATL-COLD_SATL-HOT`
## [1] 0.06907199
##
## $`SATL-COLD_Station24`
## [1] 0.03761293
##
## $`SATL-COLD_Station92`
## [1] 0.1823918
##
## $`SATL-COLD_WTRA`
## [1] 0.21589
##
## $`SATL-HOT_BRAZ`
## [1] 0.2605315
##
## $`SATL-HOT_CNRY`
## [1] 0.1658735
##
## $`SATL-HOT_FKLD`
## [1] 0.2181232
##
## $`SATL-HOT_NADR`
## [1] 0.2432495
##
## $`SATL-HOT_NAST-E`
## [1] 0.1379642
##
## $`SATL-HOT_NATR`
## [1] 0.1904544
##
## $`SATL-HOT_SATL-COLD`
## [1] 0.06907199
##
## $`SATL-HOT_SATL-HOT`
## [1] 0
##
## $`SATL-HOT_Station24`
## [1] 0.1066527
##
## $`SATL-HOT_Station92`
## [1] 0.1588125
##
## $`SATL-HOT_WTRA`
## [1] 0.1930927
##
## $Station24_BRAZ
## [1] 0.1870998
##
## $Station24_CNRY
## [1] 0.1015087
##
## $Station24_FKLD
## [1] 0.1306556
##
## $Station24_NADR
## [1] 0.1456302
##
## $`Station24_NAST-E`
## [1] 0.03867135
##
## $Station24_NATR
## [1] 0.188135
##
## $`Station24_SATL-COLD`
## [1] 0.03761293
##
## $`Station24_SATL-HOT`
## [1] 0.1066527
##
## $Station24_Station24
## [1] 0
##
## $Station24_Station92
## [1] 0.20557
##
## $Station24_WTRA
## [1] 0.2375385
##
## $Station92_BRAZ
## [1] 0.2339766
##
## $Station92_CNRY
## [1] 0.1709937
##
## $Station92_FKLD
## [1] 0.2312422
##
## $Station92_NADR
## [1] 0.2703484
##
## $`Station92_NAST-E`
## [1] 0.2439272
##
## $Station92_NATR
## [1] 0.08763472
##
## $`Station92_SATL-COLD`
## [1] 0.1823918
##
## $`Station92_SATL-HOT`
## [1] 0.1588125
##
## $Station92_Station24
## [1] 0.20557
##
## $Station92_Station92
## [1] 0
##
## $Station92_WTRA
## [1] 0.03449035
##
## $WTRA_BRAZ
## [1] 0.2459185
##
## $WTRA_CNRY
## [1] 0.1936017
##
## $WTRA_FKLD
## [1] 0.251249
##
## $WTRA_NADR
## [1] 0.2910877
##
## $`WTRA_NAST-E`
## [1] 0.275562
##
## $WTRA_NATR
## [1] 0.09419016
##
## $`WTRA_SATL-COLD`
## [1] 0.21589
##
## $`WTRA_SATL-HOT`
## [1] 0.1930927
##
## $WTRA_Station24
## [1] 0.2375385
##
## $WTRA_Station92
## [1] 0.03449035
##
## $WTRA_WTRA
## [1] 0## Permutation test for rda under reduced model
## Permutation: free
## Number of permutations: 999
##
## Model: rda(formula = ASV.clr.t.sort ~ SST + salinity + distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l. + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. + chlorophyll + altitude + azimuth, data = meta.wf.data)
## Df Variance F Pr(>F)
## Model 12 1056.8 7.1272 0.001 ***
## Residual 108 1334.5
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.4419366## Call: rda(formula = ASV.clr.t.sort ~ SST + salinity +
## distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l.
## + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. +
## chlorophyll + altitude + azimuth, data = meta.wf.data)
##
## Inertia Proportion Rank
## Total 4734.8559 1.0000
## Constrained 2774.1390 0.5859 12
## Unconstrained 1960.7169 0.4141 108
## Inertia is variance
##
## Eigenvalues for constrained axes:
## RDA1 RDA2 RDA3 RDA4 RDA5 RDA6 RDA7 RDA8 RDA9 RDA10 RDA11
## 1520.5 404.5 334.9 175.0 145.8 65.5 38.8 29.7 21.8 15.6 11.5
## RDA12
## 10.5
##
## Eigenvalues for unconstrained axes:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8
## 483.0 169.4 152.7 79.4 70.3 62.0 56.1 48.8
## (Showing 8 of 108 unconstrained eigenvalues)
##
## [1] "mean distances of sites from centroids"
## # A tibble: 11 x 2
## province mean
## * <fct> <dbl>
## 1 BRAZ 0.0418
## 2 CNRY 0.0796
## 3 FKLD 0.0414
## 4 NADR 0.0275
## 5 NAST-E 0.0495
## 6 NATR 0.0425
## 7 SATL-COLD 0.0350
## 8 SATL-HOT 0.0389
## 9 Station24 0
## 10 Station92 0
## 11 WTRA 0.0423
## [1] "distances between high/low PP province"
## $BRAZ_BRAZ
## [1] 0
##
## $BRAZ_CNRY
## [1] 0.1350259
##
## $BRAZ_FKLD
## [1] 0.111809
##
## $BRAZ_NADR
## [1] 0.04082605
##
## $`BRAZ_NAST-E`
## [1] 0.0819547
##
## $BRAZ_NATR
## [1] 0.2178716
##
## $`BRAZ_SATL-COLD`
## [1] 0.17307
##
## $`BRAZ_SATL-HOT`
## [1] 0.1997321
##
## $BRAZ_Station24
## [1] 0.1204502
##
## $BRAZ_Station92
## [1] 0.2499066
##
## $BRAZ_WTRA
## [1] 0.2481492
##
## $CNRY_BRAZ
## [1] 0.1350259
##
## $CNRY_CNRY
## [1] 0
##
## $CNRY_FKLD
## [1] 0.2293027
##
## $CNRY_NADR
## [1] 0.1758032
##
## $`CNRY_NAST-E`
## [1] 0.1644036
##
## $CNRY_NATR
## [1] 0.09379554
##
## $`CNRY_SATL-COLD`
## [1] 0.2042944
##
## $`CNRY_SATL-HOT`
## [1] 0.16301
##
## $CNRY_Station24
## [1] 0.1462429
##
## $CNRY_Station92
## [1] 0.1643611
##
## $CNRY_WTRA
## [1] 0.2057638
##
## $FKLD_BRAZ
## [1] 0.111809
##
## $FKLD_CNRY
## [1] 0.2293027
##
## $FKLD_FKLD
## [1] 0
##
## $FKLD_NADR
## [1] 0.08901738
##
## $`FKLD_NAST-E`
## [1] 0.073328
##
## $FKLD_NATR
## [1] 0.2924188
##
## $`FKLD_SATL-COLD`
## [1] 0.1409201
##
## $`FKLD_SATL-HOT`
## [1] 0.2151575
##
## $FKLD_Station24
## [1] 0.1280154
##
## $FKLD_Station92
## [1] 0.2893493
##
## $FKLD_WTRA
## [1] 0.2545043
##
## $NADR_BRAZ
## [1] 0.04082605
##
## $NADR_CNRY
## [1] 0.1758032
##
## $NADR_FKLD
## [1] 0.08901738
##
## $NADR_NADR
## [1] 0
##
## $`NADR_NAST-E`
## [1] 0.09014844
##
## $NADR_NATR
## [1] 0.2580021
##
## $`NADR_SATL-COLD`
## [1] 0.1853294
##
## $`NADR_SATL-HOT`
## [1] 0.227645
##
## $NADR_Station24
## [1] 0.1418313
##
## $NADR_Station92
## [1] 0.2846262
##
## $NADR_WTRA
## [1] 0.2747602
##
## $`NAST-E_BRAZ`
## [1] 0.0819547
##
## $`NAST-E_CNRY`
## [1] 0.1644036
##
## $`NAST-E_FKLD`
## [1] 0.073328
##
## $`NAST-E_NADR`
## [1] 0.09014844
##
## $`NAST-E_NAST-E`
## [1] 0
##
## $`NAST-E_NATR`
## [1] 0.2199759
##
## $`NAST-E_SATL-COLD`
## [1] 0.0952133
##
## $`NAST-E_SATL-HOT`
## [1] 0.1482389
##
## $`NAST-E_Station24`
## [1] 0.05876246
##
## $`NAST-E_Station92`
## [1] 0.2179625
##
## $`NAST-E_WTRA`
## [1] 0.1919901
##
## $NATR_BRAZ
## [1] 0.2178716
##
## $NATR_CNRY
## [1] 0.09379554
##
## $NATR_FKLD
## [1] 0.2924188
##
## $NATR_NADR
## [1] 0.2580021
##
## $`NATR_NAST-E`
## [1] 0.2199759
##
## $NATR_NATR
## [1] 0
##
## $`NATR_SATL-COLD`
## [1] 0.2199167
##
## $`NATR_SATL-HOT`
## [1] 0.1420305
##
## $NATR_Station24
## [1] 0.1781908
##
## $NATR_Station92
## [1] 0.09684651
##
## $NATR_WTRA
## [1] 0.1666589
##
## $`SATL-COLD_BRAZ`
## [1] 0.17307
##
## $`SATL-COLD_CNRY`
## [1] 0.2042944
##
## $`SATL-COLD_FKLD`
## [1] 0.1409201
##
## $`SATL-COLD_NADR`
## [1] 0.1853294
##
## $`SATL-COLD_NAST-E`
## [1] 0.0952133
##
## $`SATL-COLD_NATR`
## [1] 0.2199167
##
## $`SATL-COLD_SATL-COLD`
## [1] 0
##
## $`SATL-COLD_SATL-HOT`
## [1] 0.09343476
##
## $`SATL-COLD_Station24`
## [1] 0.06129151
##
## $`SATL-COLD_Station92`
## [1] 0.175991
##
## $`SATL-COLD_WTRA`
## [1] 0.119891
##
## $`SATL-HOT_BRAZ`
## [1] 0.1997321
##
## $`SATL-HOT_CNRY`
## [1] 0.16301
##
## $`SATL-HOT_FKLD`
## [1] 0.2151575
##
## $`SATL-HOT_NADR`
## [1] 0.227645
##
## $`SATL-HOT_NAST-E`
## [1] 0.1482389
##
## $`SATL-HOT_NATR`
## [1] 0.1420305
##
## $`SATL-HOT_SATL-COLD`
## [1] 0.09343476
##
## $`SATL-HOT_SATL-HOT`
## [1] 0
##
## $`SATL-HOT_Station24`
## [1] 0.08948328
##
## $`SATL-HOT_Station92`
## [1] 0.08257144
##
## $`SATL-HOT_WTRA`
## [1] 0.04892161
##
## $Station24_BRAZ
## [1] 0.1204502
##
## $Station24_CNRY
## [1] 0.1462429
##
## $Station24_FKLD
## [1] 0.1280154
##
## $Station24_NADR
## [1] 0.1418313
##
## $`Station24_NAST-E`
## [1] 0.05876246
##
## $Station24_NATR
## [1] 0.1781908
##
## $`Station24_SATL-COLD`
## [1] 0.06129151
##
## $`Station24_SATL-HOT`
## [1] 0.08948328
##
## $Station24_Station24
## [1] 0
##
## $Station24_Station92
## [1] 0.1613934
##
## $Station24_WTRA
## [1] 0.1340738
##
## $Station92_BRAZ
## [1] 0.2499066
##
## $Station92_CNRY
## [1] 0.1643611
##
## $Station92_FKLD
## [1] 0.2893493
##
## $Station92_NADR
## [1] 0.2846262
##
## $`Station92_NAST-E`
## [1] 0.2179625
##
## $Station92_NATR
## [1] 0.09684651
##
## $`Station92_SATL-COLD`
## [1] 0.175991
##
## $`Station92_SATL-HOT`
## [1] 0.08257144
##
## $Station92_Station24
## [1] 0.1613934
##
## $Station92_Station92
## [1] 0
##
## $Station92_WTRA
## [1] 0.08086013
##
## $WTRA_BRAZ
## [1] 0.2481492
##
## $WTRA_CNRY
## [1] 0.2057638
##
## $WTRA_FKLD
## [1] 0.2545043
##
## $WTRA_NADR
## [1] 0.2747602
##
## $`WTRA_NAST-E`
## [1] 0.1919901
##
## $WTRA_NATR
## [1] 0.1666589
##
## $`WTRA_SATL-COLD`
## [1] 0.119891
##
## $`WTRA_SATL-HOT`
## [1] 0.04892161
##
## $WTRA_Station24
## [1] 0.1340738
##
## $WTRA_Station92
## [1] 0.08086013
##
## $WTRA_WTRA
## [1] 0## Permutation test for rda under reduced model
## Permutation: free
## Number of permutations: 999
##
## Model: rda(formula = ASV.clr.t.sort ~ SST + salinity + distance_to_province_boundary.km. + Distance_coast.km. + oxygen.umol.l. + NO3_umol.l + PO4_umol.l + Total.N..nmol.L. + Total.C..nmol.L. + chlorophyll + altitude + azimuth, data = meta.wf.data)
## Df Variance F Pr(>F)
## Model 12 2774.1 12.734 0.001 ***
## Residual 108 1960.7
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] 0.5858972
source("C:/Users/choerstm/Documents/core_PS113/Genomics/RScripts/procrustes_RDA.R")##
## Call:
## procrustes(X = RDA_meta_autoeuk, Y = RDA_meta_autoprok)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 284.0543
## Procrustes root mean squared error:
## 1.532174
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.04660017 0.74470228 1.10494466 1.59738381 3.72292289
##
## Rotation matrix:
## [,1] [,2]
## [1,] 0.99731623 0.07321434
## [2,] -0.07321434 0.99731623
##
## Translation of averages:
## [,1] [,2]
## [1,] -1.38979e-16 1.502036e-16
##
## Scaling of target:
## [1] 1.046018
##
##
## Call:
## procrustes(X = RDA_meta_autoeuk, Y = RDA_mixo)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 498.2499
## Procrustes root mean squared error:
## 2.029228
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.2146121 1.0367862 1.6205343 2.3344760 4.2842461
##
## Rotation matrix:
## [,1] [,2]
## [1,] -0.8538392 0.5205369
## [2,] 0.5205369 0.8538392
##
## Translation of averages:
## [,1] [,2]
## [1,] -8.988767e-17 1.060911e-16
##
## Scaling of target:
## [1] 0.9578508
##
##
## Call:
## procrustes(X = RDA_meta_autoeuk, Y = RDA_heteuk)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 281.9448
## Procrustes root mean squared error:
## 1.526474
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.2160351 0.7670926 1.1809898 1.8439369 3.0814324
##
## Rotation matrix:
## [,1] [,2]
## [1,] 0.99923265 -0.03916778
## [2,] 0.03916778 0.99923265
##
## Translation of averages:
## [,1] [,2]
## [1,] -1.323376e-16 -9.267717e-17
##
## Scaling of target:
## [1] 0.642042
##
##
## Call:
## procrustes(X = RDA_meta_autoeuk, Y = RDA_hetprok)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 182.2156
## Procrustes root mean squared error:
## 1.227157
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.02882895 0.39719298 0.78175671 1.41728344 3.18014983
##
## Rotation matrix:
## [,1] [,2]
## [1,] 0.99980000 -0.01999875
## [2,] 0.01999875 0.99980000
##
## Translation of averages:
## [,1] [,2]
## [1,] 1.358923e-16 -1.365193e-16
##
## Scaling of target:
## [1] 0.5696676
##
##
## Call:
## procrustes(X = RDA_mixo, Y = RDA_meta_autoprok)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 99.89712
## Procrustes root mean squared error:
## 0.9086231
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.02435698 0.39610283 0.73182907 1.14670469 1.67876386
##
## Rotation matrix:
## [,1] [,2]
## [1,] -0.9032267 0.4291637
## [2,] 0.4291637 0.9032267
##
## Translation of averages:
## [,1] [,2]
## [1,] 3.923019e-17 6.132705e-20
##
## Scaling of target:
## [1] 0.718806
##
##
## Call:
## procrustes(X = RDA_mixo, Y = RDA_heteuk)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 89.94109
## Procrustes root mean squared error:
## 0.862157
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.06257738 0.41636444 0.61632174 0.96538773 2.16214597
##
## Rotation matrix:
## [,1] [,2]
## [1,] -0.9656681 0.2597790
## [2,] 0.2597790 0.9656681
##
## Translation of averages:
## [,1] [,2]
## [1,] -1.82302e-17 -1.576664e-16
##
## Scaling of target:
## [1] 0.4488599
##
##
## Call:
## procrustes(X = RDA_mixo, Y = RDA_hetprok)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 259.6793
## Procrustes root mean squared error:
## 1.464961
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.2978063 0.9019145 1.2785706 1.8059026 2.6899469
##
## Rotation matrix:
## [,1] [,2]
## [1,] -0.9406828 0.3392873
## [2,] 0.3392873 0.9406828
##
## Translation of averages:
## [,1] [,2]
## [1,] -1.140911e-16 -8.426021e-17
##
## Scaling of target:
## [1] 0.2192863
##
##
## Call:
## procrustes(X = RDA_heteuk, Y = RDA_meta_autoprok)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 291.5543
## Procrustes root mean squared error:
## 1.552269
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.09634701 0.85648209 1.31230100 1.91399109 3.18121830
##
## Rotation matrix:
## [,1] [,2]
## [1,] 0.9874982 0.1576302
## [2,] -0.1576302 0.9874982
##
## Translation of averages:
## [,1] [,2]
## [1,] -2.522429e-17 3.620665e-16
##
## Scaling of target:
## [1] 1.439985
##
##
## Call:
## procrustes(X = RDA_heteuk, Y = RDA_hetprok)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 559.4055
## Procrustes root mean squared error:
## 2.15016
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.4737693 1.3786705 1.9304429 2.4262950 4.1121929
##
## Rotation matrix:
## [,1] [,2]
## [1,] 0.99852602 -0.05427513
## [2,] 0.05427513 0.99852602
##
## Translation of averages:
## [,1] [,2]
## [1,] 2.805981e-16 2.234791e-17
##
## Scaling of target:
## [1] 0.6179586
##
##
## Call:
## procrustes(X = RDA_meta_autoprok, Y = RDA_hetprok)
##
## Number of objects: 121 Number of dimensions: 2
##
## Procrustes sum of squares:
## 208.9777
## Procrustes root mean squared error:
## 1.314187
## Quantiles of Procrustes errors:
## Min 1Q Median 3Q Max
## 0.1026728 0.4383279 0.9620290 1.7043480 2.7731893
##
## Rotation matrix:
## [,1] [,2]
## [1,] 0.9787671 -0.2049756
## [2,] 0.2049756 0.9787671
##
## Translation of averages:
## [,1] [,2]
## [1,] 1.554134e-16 -2.433344e-16
##
## Scaling of target:
## [1] 0.3791993## Warning: Removed 6 rows containing non-finite values (stat_contour).## Warning: Removed 2 rows containing missing values (geom_point).
